Crowdsourcing the crowd: activities and the right crowd to source.
A qualitative research on how crowdsourcing activities influence the innovation process of Dutch hospitals.
Master Thesis
University of Amsterdam: MSc Business Administration – Entrepreneurship & Innovation Track: Entrepreneurship & Innovation
Student: Anne Elisa Sant Student number: 11414529 Supervisor: Alexander Alexiev Date: June 23, 2017
Statement of originality
This document is written by Anne Sant who declares to take full responsibility for the content of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the content.
Table of content Abstract 4 Introduction 5 Crowdsourcing in the health care sector 7 Research Objective 8 Research Question 8 Thesis Structure 10 Literature review 11 Innovation and innovation processes in the health care sector 11 Crowdsourcing and the innovation process 13 Assumptions & conceptual model 16 ‘The Crowd’ for crowdsourcing 17 Crowdsourcing knowledge 19 The need to innovate: gaining competitive advantage 19 Influencers of the innovation process 20 Characteristics 20 Implementation of the innovation 21 Top-down or bottom-up 21 Reimbursement strategy 22 Technology adoption 22 Intellectual Property 23 Data security 24 Advanced conceptual model 24 Methodology 25 Design and scope 25 Data collection & sample 26 Strengths and limitations of the research design 28 Analyses Strategy 29 Results 30 Influence of crowdsourcing on the innovation process 30 Idea generation phase 30 Research phase 34 Development phase 37 Commercialisation phase 41 General Barriers 44 The ‘crowd’ or parties involved 46 Framework 49 Discussion 50 Influence of crowdsourcing on the innovation process of Dutch hospitals 50 The crowd for crowdsourcing in the clinical environment of Dutch hospitals 55 Barriers for crowdsourcing to innovate 56 Innovation process phases 57 Contributions and limitations 57 Conclusion 59 References 61 Appendices 67 Appendix 1: Word map: from interviews made in NVivo 67 Appendix 2: Node tree 68
Open innovation & crowdsourcing 69 Network effects 69 Possible influences of external crowdsourcing on the innovation process 70 Appendix 5: extra tables from results section 71 Appendix 6: Interview Questions 81 Questionnaire for specialists within hospitals: 81 Questionnaire for clinical partners 84 Appendix 7: Transcript of the interviews 87
Abstract
This research investigates the influence of crowdsourcing activities on the innovation process of Dutch hospitals. Different phases of the innovation process are distinguished and the influence of crowdsourcing on the specific phases will be taken into account. Attention is given to the crowds that are involved in the crowdsourcing activities for the different phases of the innovation process. The central question in this research is: “How is the innovation process of Dutch hospitals influenced by the use of crowdsourcing?” This question will be answered by framing the innovation process within health care organisations and the influence of crowdsourcing on this innovation process. Thus, the clinical as well as the innovation environment of Dutch hospitals will be investigated. Different theories from academic literature will be used to come to a conceptual model to research how the innovation process of Dutch hospitals is influenced when crowdsourcing to innovate. The field research will be done through interviews with different specialist actors from specific hospitals that will be used as a multiple case study for this research. Next to this, the needed information about the clinical environment of Dutch hospitals in relation with technological vendors and crowdsourcing possibilities for hospitals will be retrieved from clinical experts from company Royal Philips.
Keywords: crowdsourcing – innovation – external innovation - open innovation – innovation process – Dutch hospitals - specialists
Introduction
“The power of crowdsourcing always remains with the crowd, not the technological implementation (Goodreads - Jay Samit, 2017).” This quote from one of the world’s leading
experts on disruption and innovation emphasises the impact that the crowd can have in a crowdsourcing process. An early definition of crowdsourcing is the act of taking a challenge faced by a firm and, instead of asking internal research and development departments to solve the challenge, the firm broadcasts an open call to individuals with relevant expertise outside the firm to become involved in solving the challenge (Howe, 2006). Nowadays organisations are increasingly using crowdsourcing initiatives to innovate, and this is the case for the health care sector in the Netherlands.
According to Swan (2012), accessing the crowd sourced cohorts for health studies is a significant opportunity that could have a stimulating impact on public health research, particularly as outcomes move to the personalized, preventive medicine of the future. Furthermore, Salge, Farchi, Barrett and Dopson (2013) argue that, given the growing popularity of the open innovation model, it is increasingly common to source knowledge for new product ideas from a wide range of actors located outside of organisational boundaries. Such open search strategies, however, might not always be superior to their closed counterparts. Indeed, widening the scope of knowledge sourcing during the early stages typically comes at a price given the substantial monetary and nonmonetary costs often incurred in the process of identifying, assimilating, and using external knowledge input. Salge et al. focus on the source of knowledge for new product ideas, but sourcing does not have to only apply in the idea generation phase.
The Dutch Authority for Consumers and Markets (ACM) has announced the collaboration plans of six Dutch hospitals that wish to bring their care for breast cancer
are not each other’s direct competitors. The hospitals wish to develop a standardized approach to high-quality breast cancer care. Their plan is to negotiate collectively with health insurers (ACM, 2015). In the past few years there has been an increase in collaboration between the health care sector, Dutch hospitals in particular, and market companies (e.g. technological or development companies). The aforementioned example can be seen as a form of crowdsourcing, and this method could in turn influence the innovation processes within Dutch hospitals.
Such collaboration between Dutch hospitals and market companies could enhance the quality and efficiency of the branch of medical specialist care, and can be used to come to a transparent, nationwide service (ACM, 2015). The hospitals collaborating have jointly agreed upon a standardized approach with regard to breast cancer care, which they consider to be of excellent quality. According to the hospitals involved, multiple stakeholders such as patients, consumers and market companies will benefit from this collaboration (ACM, 2015).
In the last decade, the World Wide Web has evolved into a powerful medium for active collaboration among people on a global scale. Many successful examples exist of people coming together on the Web to combine their resources. This can include knowledge, creativity, opinions, skills, and more resources (Geiger, Seedorf, Schulze, Nickerson & Schader, 2011). In addition, Johnston & Hauser (2009) found that the internet has spawned a revolution in collaboration. With more people contributing, the productivity, efficiency, and creativity may all increase.
One central idea behind the concept of open innovation is that firms can reduce their research and development costs by incorporating external knowledge (Chesbrough & Appleyard, 2007). From this perspective, it is accepted that firms will be able to capture value from knowledge produced outside the firm. This is not easy to implement, however, as the information generated is the result of collective creativity carried out within communities of
associates who are external to the organisation (Chanal & Caron-Fasan, 2010). When considering costs, the actual sourcing of information can also play a significant role.
The characteristics of companies’ relationships influence what happens inside the companies themselves (Håkansson & Ford, 2002). Opportunities and limitations for a company are related both to the resources invested in relationships and to the companies’ internal capabilities. All companies’ relationships and resources can be developed and combined with others in a large number of different ways. This creates major opportunities for innovation, to the benefit of both the organisations that seize them (Håkansson & Ford). Crowdsourcing in the health care sector
Crowdsourcing is emerging as an open-innovation approach to promote collaboration and to harness the complementary expertise of academic and industrial partners in the early stages of drug discovery. Greater collaboration between academic institutions and the pharmaceutical industry is increasingly being pursued to access and foster innovation in the early stages of drug discovery. The hope is that such collaborations could help to address the need to improve research and development productivity in the industry, and also enable academic institutions to more effectively exploit the translational potential of their research (Lessl, Bryans, Richards & Asadullah, 2011).
There have been crowdsourcing initiatives taking place in the early stages of drug discovery. In contrast to the classical concept of crowdsourcing, in which the task is finished once the solution has been provided, the goal of these initiatives is to seek novel ideas that are then pursued further in a more collaborative approach. The key benefits are that potential solvers, most of whom are researchers in academic institutes or small companies, gain access to specific tools or knowledge, such as data or compounds or drug discovery expertise in large pharmaceutical companies, whereas the searching organisation gains novel ideas, targets,
Whitehouse et al. (2013) there are significant practical challenges of embedding the development of e-Health technology within a research environment. They see challenges in the implementation of the development. In an ideal world, there would be better mechanisms to support long-term research collaborations between industry and academic institutions such as crowdsourcing activities.
Research Objective
The practical influence of crowdsourcing on the innovation phases of Dutch hospitals has not yet received considerable research attention. The objective of this research is to explore the influence of crowdsourcing on the different phases of the innovation process of Dutch hospitals in practice. To enable this, assumptions are drawn based on a conceptual model. In addition to describing the influence of crowdsourcing on the different phases of the innovation process, this research further aims to provide insights into the general innovation processes of hospitals.
Research Question
Previous research has investigated the innovation processes themselves, the crowdsourcing processes to choose the right crowd and remuneration methods. For example Geiger et al. (2011) provide a framework for crowdsourcing processes. This framework is uniquely focuses from an organisational perspective. They identified four dimensions that describe how crowdsourcing processes differ. Other academic research has looked at the motives for participating in crowdsourcing. Piezunka & Dahlander (2015) contribute to the literature on crowdsourcing by examining the stages that follow the sourcing of suggestions. They show that organisations might fail to harness the full potential of crowdsourcing due to inadequate filtering mechanisms. Piezunka & Dahlander (2015) suggest that scholars of crowdsourcing should examine the phases subsequent to the sourcing itself. Related to the case study, this is also a subject that could be further researched. So far, most research on innovations in health
care has been focused on individual doctors working independently in small practices, such as general practitioners working with guidelines. Less is known about the determinants of innovations in larger health care organisations, which may be different from those of innovations for individual health care professionals (Fleuren, Wiefferink & Paulussen, 2004.)
The academic literature describes a broad range of definitions and mechanisms of open innovation and crowdsourcing in particular in the health care sector but a description of the influence of crowdsourcing on the innovation process phases is still neglected. The lack of insight into the process of crowdsourcing and a description of the influence of crowdsourcing on the different phases of the innovation processes of hospitals can be seen as gap in the literature. A clear framework that describes the influence of crowdsourcing on the innovation process of hospitals can address this literature gap. This leads to the following research question:
“How is the innovation process of Dutch hospitals influenced by the use of crowdsourcing?”
For this research question, a framework that combines the insights from earlier research with the prevailing relationships between crowdsourcing and the innovation process in hospitals in practice is build. A conceptual framework permits comparing, contrasting and integrating of these various perspectives. Addressing this research question is important because in the long run it might guide a hospitals’ decision whether or not to use external crowdsourcing initiatives in which the hospital wishes to innovate. Before answering the question how the innovation process of Dutch hospitals is influenced by the use of crowdsourcing, it is important to map the current innovation process at these hospitals. From the literature a general innovation process can be retrieved, but there is little academic literature that describes the innovation process within Dutch hospitals. It might even be questioned if they
conducted that addresses in which phases of the innovation process Dutch hospitals and professionals in the field could benefit from crowdsourcing initiatives, and how this influence is reflected in practice. This leads to the following sub questions:
1. How does the innovation process look like for Dutch hospitals that use crowdsourcing activities to innovate?
2. What are influencers of the innovation process that could impact the different innovation phases of Dutch hospitals when using crowdsourcing activities to innovate?
3. How does collaboration with ‘the crowd’ or external partners influence the different phases of the innovation process within Dutch hospitals in practice?
Before mapping the clinical terrain, it is important to have a good overview of the current external crowdsourcing domain of Dutch hospitals. The practicalities of the phases within the innovation process in the health care sector must be clear in order to elaborate on this for deciding on the influence of the crowdsourcing process. Lastly, it is important to explore the clinical environment of Dutch hospitals with regard to open innovation. Both Dutch hospitals and external parties have to know in what phases of the innovation process there might be chances for collaboration through crowdsourcing.
Thesis Structure
First, this research will provide a literature review that explains the main concepts used in this research. The innovation process at Dutch hospitals will be investigated. Namely, it will be researched how the open innovation environment is arranged in the health care sector. Based on these findings there will be research on where in the innovation process Dutch hospitals could best use crowdsourcing to innovate. Based on the literature, a conceptual model to investigate these phases and the influence of crowdsourcing on the innovation process will be
provided. Secondly, the research methodology will follow. In this section the design and scope of the research, the data collection method, sample analysis method and the strengths and limitations of the research design will be explained. Next, the analysis section will present the empirical results that will lead to the discussion. Thereafter, a conclusion, recommendations and limitations will follow.
Literature review
The literature review identifies important aspects of crowdsourcing and the innovation process for further understanding of these concepts, and how they relate with connected views. This will lead to a series of assumptions that are shown in a conceptual model. In this section, a comparative analysis of the academic literature will be conducted to identify possible influencers of the innovation process through crowdsourcing at hospitals.
Innovation and innovation processes in the health care sector
Innovation processes in the health care sector contribute significantly to the continuous development of the industry. With product lifecycles that are sometimes as short as 18 months, patients benefit from an on-going stream of innovation that relies heavily on successful needs assessment and the knowledge and skill set of engineers and other professionals involved in the innovation process (Pietzsch, Shluzas, Paté-Cornell, Yock & Linehan, 2009). In this research, the definition of Fleuren et al. (2004) will be used to determine the concept of innovation. They describe innovation as an idea, practice, or object that is perceived as new by an individual or other unit of adoption. Moreover, Fleuren et al. argue that several factors can affect the process, positively or negatively, and sometimes changes do not occur because health professionals do not accept the innovation or insufficient financial sources are made available to implement the innovation. Majchrzak and Malhotra
solutions to a complex problem posed by the organisation sponsoring the challenge call. Innovative solutions are those that are novel and implementable for the sponsoring organisation.
To structure the internal innovation processes, some phases should be determined. Rohrbeck, Hölzle & Gemünden (2009) differentiate four categories that follow the innovation process stages. The first category or phase is the idea generation phase that includes any sources and activities that contribute to the development of a new innovation. Secondly, Rohrbeck et al. indicate the research phase in which tools are directed at facilitating research collaboration or adapting technologies. Thirdly, they distinguish the development phase of an organisation, where the activities are aimed at engaging with partners in the creation of new products or new services. Lastly, the commercialization phase is focused on activities that engage with external partners to bring technologies, products or services to the market. This can be from the hospital perspective to sell their innovation to other hospitals but also from external parties that have developed a prototype or innovation for a particular hospital. The phases described by Rohrbeck et al. will be used throughout this research. They will be further discussed when the influence of crowdsourcing on the innovation process will be taken into account.
Kanter (2002) also distinguish four primary tasks of the innovation process. According to him these tasks include idea generation, coalition building, idea realization (prototype production), and diffusion (commercialization of the product). These tasks can be related to the previously mentioned phases of the innovation process. Kanter (2000) argues that structural connections between potential innovators and users are involved in the innovation process, as well as the structural connections between the innovation and the organisations that will commercialize the innovation. Next to these four phases the intensity of the processes can be taken into account in practice. The intensity consists of different factors,
such as the budget that is available for the specific activity or phase, the time that is put into the process and the resources that are available.
Crowdsourcing and the innovation process
Given the growing popularity of the open innovation model, it is increasingly common to source knowledge for new product ideas from a wide range of sources located outside of organisational boundaries. Crowdsourcing for innovation has been used to obtain ideas, technologies, and even entire businesses from outside the organisation (Howe, 2006).
Following the first definition of crowdsourcing from Howe, in general, Seltzer & Mahmoudi (2012) state that crowdsourcing is most applicable to problems where needed expertise and knowledge is lacking from the firm. In the academic literature on innovation, crowdsourcing can be seen as a particular form of “open innovation” (Rouse, 2010). Open innovation, taken from the fields of business strategy and technology development, can offer planners fresh insights into their own practice. Open innovation goes outside the boundaries of the organisation to find solutions to problems and to hand ideas off to partners. A key technique for open innovation is ‘‘crowdsourcing’’ which is explained as issuing a challenge to a large and diverse group in hopes of arriving at new solutions more robust than those found inside the organisation (Seltzer & Mahmoudi, 2012).
Simply defined, crowdsourcing represents the act of a company or institution taking a function once performed by employees and outsourcing it to an undefined network of people in the form of an open call. This can take the form of peer-production (when the 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 (Celi, Ippolito, Montgomery, Moses & Stone, 2014).
applicable on a broader set of institutional and infrastructural arrangements in open innovation, for example crowdsourcing platforms. Crowdsourcing as an open innovation practice requires managers to rethink managerial and governance structures that facilitate the flow of knowledge across firm boundaries, motivating participants, and appropriate rents from the practice. Managers must also align their own organisational governance practices to those of outside sources, also depending on whether crowdsourcing takes place directly or through an intermediary or whether it is tournament based or collaboration based (Bogers et al.).
Katila and Ahuja (2002) found that using and reusing existing internal knowledge fosters the generation of new products, but beyond a certain point the additional exploitation of internal expertise will lead to a drop in new product output. Contrary to their expectations, they also found that the extent to which a firm explores external information is positively related to successful new product innovation. Kanter (2000) states that inter-organisational ties and organisation-environment connections facilitate and enrich the innovation process. The crowdsourcing and open data development present an opportunity to involve frontline providers and patients in accelerating innovation, including knowledge creation (Celi et al., 2014). Embedding user-driven research and development into communities can create connections that accelerate and enhance the innovation process, increasing the speed and effectiveness of the dissemination of a solution or new knowledge (Celi et al., 2014). Thus by creating these connections this could improve the innovation process. This underlines the effectiveness of crowdsourcing for innovation. Affuah and Tucci (2012) also found that crowdsourcing might be a better mechanism for solving problems than internal sourcing or designated contracting.
A critical note from Aitamurto, Leiponen, and Tee (2011) is that crowdsourcing can be problematic when the problem sent to the crowd is poorly defined, and when there is less
to no feedback that enables the crowd to adapt better in pursuit of finding solutions. In contrast, Aitamurto et al. also find that crowdsourcing can be both economically and intellectually a fruitful activity, but firms may need to be realistic about what types of problems and users they can feasibly engage, and what capabilities they have or need to manage the community and its expectations.
Some researchers typically investigate crowdsourcing for the idea generation phase of innovation processes, as seen above. Instead, Celi et al. (2014) state that individual users should not have to build everything from scratch or set up a database on their own: they benefit from collaborating with those who have the capabilities that they lack or building on solutions developed by and freely shared by others. Thus, according to Celi et al., the crowdsourcing process can influence the idea generation phase, the development phase and commercialisation phase. Furthermore, recent work suggests that crowdsourcing may be more appropriate at later stages of the technological lifecycle and is subject to other contingencies including the context of networks, industry and geography (Bogers et al., 2016).
Even though many open innovation practices are based on the crowdsourcing principle, these practices differ significantly in terms of the type of knowledge exchanged. Ideation contests, for example, require only limited disclosure of sensitive information by the focal firm and are primarily used for the acquisition of information about customer needs and preferences during the first stages of the innovation process. Tournament-based crowdsourcing in the context of technical problem solving, on the contrary, requires not only the participation of other internal organisational units (research and development), but also seeks a different type of knowledge, solution and information in a later stage of the innovation process (Lüttgens, Pollok, Antons & Piller, 2014).
Assumptions & conceptual model
From the literature about innovation processes in the health care sector it is clear what phases can be described within the innovation process, but the practical influence of the crowdsourcing concept in this area remains ambiguous. The external parties involved in different phases of the innovation process also need further research attention. These findings based on the literature can be explained with the use of a conceptual model. Several assumptions are made based on the literature framework.
A1: The hospitals have a certain innovation process with different phases
A2: Hospitals collaborate with external parties through crowdsourcing initiatives to foster innovation.
A3: The innovation process phases of hospitals that engage in crowdsourcing activities will be influenced by these activities.
A4: Actors in Dutch hospitals and the clinical environment of hospitals see potential in collaboration through crowdsourcing initiatives to stimulate innovation.
The conceptual model is based on an integration of the scholarly literature regarding crowdsourcing and innovation and the stated assumptions, to visualize what will be tested.
Figure 1: conceptual model: the influence of the crowdsourcing process on the innovation phase(s) of hospitals.
Crowdsourcing
?
Idea generation
phase Research phase Development phase Commercialization phase
'Crowd' involved ? Crowdsourcing ? 'Crowd' involved ? Crowdsourcing ? Crowdsourcing ? 'Crowd' involved ? 'Crowd' involved ?
In the remaining part of this section, further related concepts and relationships with regard to the influence of crowdsourcing on the innovation process will be elaborated upon. This entails the possible crowd for crowdsourcing activities of hospitals, the aim of crowdsourcing, the need for innovation activities, and influencers of the innovation process that could be relevant for the execution of crowdsourcing. These influencers and the possible crowd for crowdsourcing will be combined with the conceptual model in figure 2.
‘The Crowd’ for crowdsourcing
The crowd is generally composed of heterogeneous individuals. In particular, a crowd may be composed of scientists and experts in various fields, but also of novices. While many individuals may work simultaneously on a given project, the client firm will eventually choose the outcome that best meets its needs (Schenk & Guittard, 2011). In order to continually innovate, firms are opening their boundaries to engage external expertise (Majchrzak & Malhotra, 2013). Instead of simply collaborating with a select few known external parties, firms are increasingly innovating using ‘crowdsourcing’. Sometimes, participants in crowdsourcing are limited to specifically selected communities. Alternatively, the general public is invited (Majchrzak & Malhotra, 2013).
Relationships enable companies to cope with their increasing technological dependence on others, and the need to develop and tailor offerings to more specific requirements (Håkansson & Ford, 2002). The relevance of customers and suppliers in emerging technologies, in which the tangible part of the product or service offering is still to be developed, may be less significant. Johnsen, Phillips, Caldwell & Lewis (2006) agree with this and argue that suppliers may have a relatively limited role to play in the early stages of the innovation process where the product or service offering is still experimental and industry-wide standards are yet to be established. They suggest that key suppliers that may be
centres and consultants, rather than material or component suppliers. In such settings, horizontal interaction with, for example, universities and research centres may be far more critical (Johnsen et al., 2006).
Technological vendors such as Siemens and Royal Philips are specialized in technological innovations. Royal Philips is a diversified technology company, focused on improving people’s lives through innovation. The health care business accounts for 42 per cent of their global sales revenue. With about one hundred years of history and more than 450 innovative products and services, Royal Philips is meeting challenges in the health care industry by creating solutions that deliver better care to more people at lower cost (Philips, 2017). The mission of Royal Philips Innovation Services is to accelerate innovation, inside and outside Royal Philips, from start-ups to multinationals (Philips, 2013). Product or process distinctions help to understand the application of innovations, either as a new product offering unique benefits to customers, or as an improvement in the production or delivery of existing products. Technical innovations are defined as pertaining to ‘products, services, and production process technology; they are related to basic work activities and can concern either product or process’. On the other hand, administrative innovations, which may be technology-based, ‘involve organisational structure and administrative process; they are indirectly related to the basic work activities of an organisation’ (McDonald & Srinivasan, 2004).
According to Bogers et al. (2016), attention needs to be paid to the possible differences between stakeholders, as they may bring about heterogeneous factors contributing to the effectiveness of open innovation. One important difference is the kind of input that is provided by the external parties, ranging from needs, demands, and ideas to solutions to problems, designs, and patents. It appears fruitful to address both the nature of external stakeholders’ contributions, as well as the innovation process steps in which they are involved (Bogers et al.).
Crowdsourcing knowledge
According to Celi et al. (2014), clinicians are typically busy with their daily practice, so much that they do not recognize or act on ways to improve the creation of new ideas or knowledge. Researchers may not be able to identify the gaps in clinical knowledge. For data scientists, the main challenge is discerning what is relevant in a domain that is both unfamiliar and complex. Each type of domain expert can contribute skills unavailable to the other groups. “Health hackathons” and “data marathons”, in which diverse participants work together, can leverage the current availability of digital data to discover new knowledge. Utilizing the complementary skills and expertise of these talented and functionally divided groups, innovations are formulated at the systems level. As a result, the knowledge discovery process is simultaneously democratized and improved, real problems are solved, cross-disciplinary collaboration is supported, and innovations are enabled (Celi et al., 2014).
Crowdsourcing knowledge discovery in medicine can be vertically approached by lowering the barriers of participation to frontline providers and horizontally approached by extending an input role to non-traditional but interested contributors such as patients themselves. When applied to innovations in general, this process would permit people interacting with the medical system to develop exactly what they want, rather than relying on manufacturers to act as their agents (Celi et al., 2014).
The need to innovate: gaining competitive advantage
The reduction of costs and gaining competitive advantage is often related with the resource-based view. Resource-resource-based theory takes the perspective that valuable, costly-to-copy firm resources and capabilities provide the key sources of sustainable competitive advantage (Hart, 1995). The resource-advantage theory of competition describes how an organisation with lower relative resource cost can achieve a position of competitive advantage if it offers equal
impact of developed innovations addresses the strategic utility of innovations to achieve or maintain a position of competitive advantage (McDonald & Srinivasan, 2004). This underlines the need of hospitals to innovate. Garcia and Calantone (2002) mention that it is important that an invention does not become an innovation until it has processed through production and marketing tasks and is diffused into the marketplace. This indicates that the process is important for an innovation to become one.
Crowdsourcing for innovation in itself is not a new concept but the move towards open innovation and innovation as a strategic competitive advantage for the organisation has increased its focus by academics (Majchrzak & Malhotra, 2013). Afuah and Tucci (2012) found that under certain circumstances crowdsourcing transforms distant search into local search, thus enabling firms to take advantage of the many benefits of distant search without having to endure many of its costs. The relationship between open innovation and crowdsourcing can help to better understand the relationship between openness and firm performance (Bogers et al., 2016). McDonald and Srinivasan (2004) argue that the innovations themselves may lead to positions of competitive advantage, but the adopting organisation’s capabilities and competences are more likely to lead to sustainable positions of competitive advantage.
Influencers of the innovation process
Characteristics
Fleuren, Wiefferink and Paulussen (2004) found several determinants that influence the stages of the innovation process of health care organisations. They divide these into different characteristics that are: characteristics of the social-political context (this includes rules, regulation and patient characteristics), characteristics of the organisation (for example the employee turnover or the decision making process within the organisation), characteristics of the adopting person (or user of the innovation, this includes knowledge, skills and perceived
support from colleagues) and characteristics of the innovation (including complexity and relative advantage). Together these are the characteristics of the innovation strategy that could influence the innovation process phases. From these characteristics, specific attributes are processed in the interview questions related to crowdsourcing and the innovation process within specific hospitals to stimulate a description of the specific influence of crowdsourcing on the innovation process. In addition, different people may have different degrees of power to influence the process as well as different individual appreciations of the same risks and benefits (Denis, Hébert, Langley, Lozeau, & Trottier, 2002).
Implementation of the innovation
An innovation that appears well defined in theory can prove to be much less well defined when implementation issues are considered. Such issues include questions about the intensity of follow up, the organisation responsible, the location of patient training, among others (Denis et al., 2002). The implementation of the innovation and the degree in which specialists know how to work with the new innovation are taken into account in the interviews to investigate the influence of crowdsourcing on the different phases of the innovation process of Dutch hospitals.
Top-down or bottom-up
Thakur, Hsu & Fontenot (2012) argue that to roll out innovation in an effective way management should maintain a positive relationship with their employees. They also state that, to maintain such relationships, management should engage in extensive information sharing across organisational levels by applying a bottom–up approach rather than emphasizing a top–down approach. A bottom–up approach is defined as the flow of information from a lower level to a higher level. Furthermore Thakur et al. state that to effectively trickle a culture of innovation within an organisation, health care executives and
(Thakur, Hsu & Fontenot, 2012). With this mind, the relationship between higher and lower levels within the hospitals is taken into account in conducting this research.
Reimbursement strategy
In order to commercialize a medical device, companies often develop an early-stage reimbursement strategy. It is critical for companies to determine what will be required to secure a payment strategy, and how long it might take to implement such a strategy: “Understanding potential reimbursement rates is also imperative for effectively pricing a new product. Particularly in medical devices, where the lifecycle from concept to launch is relatively short, entrepreneurs need to develop plans and processes to obtain reimbursement coverage prior to market entry. This is important to facilitate market acceptance and help generate increased demand” (Pietzsch et al., 2009). Introducing a new product successfully is highly complex, and depends heavily on the implementation of rigorous processes. These processes need to allow developers to optimally phase development, testing, and other activities, and to successfully execute on the manifold requirements of third parties, including regulators and payers. These additional requirements set medical device development apart from the development of other products (Pietzsch et al., 2009). Therefore, before the commercializing phase, there should be a reimbursement strategy developed for innovation on medical devices.
Technology adoption
Garcia & Calantone (2002) state that ‘Innovation’ from an overall perspective is best captured by an iterative process initiated by the perception of a new market and/or new service opportunity for a technology- based creation that leads to development, production, and marketing tasks striving for the commercial success of the creation.
According to the technology acceptance model (TAM) of Thakur, Hsu and Fontenot (2012) there are two important factors that drive a customer's intention to adopt a new
technology. They state that perceived ease of use and perceived usefulness of the technology are the antecedents for technology adoption. Equivalently, in the clinical context, if the healthcare executives and practitioners are familiar with the technology, one can assume that they will find the technology to be useful and it will be easier to use by decreasing their fear and uncertainty in using the technology. The result of the diminished ambivalence and fear is the enhancement of intention to adopt the technology (Thakur, Hsu & Fontenot, 2012). This could enable the healthcare organisation to implement the crowd sourced innovative ideas within the organisation. On-the-job-training to keep healthcare executives and employees up to date would increase their familiarity with technology and enhance their likelihood of adopting new information technology or information systems. Their innovativeness and ingenuity would enhance their capacity to implement an innovation (Thakur, Hsu & Fontenot, 2012).
Intellectual Property
To be able to use any submitted idea, the organisation will need to ensure that it receives access or ownership rights. The key mechanism to enable this transfer is the use of terms and conditions for submitters (Alexy, Criscuolo & Salter, 2012). Idea competitions are mainly conducted online, which means that the effort of both the organizer and the participant is relatively low and that a lot of people, virtually from around the globe, have access to the initiative. The intellectual property of the submitted ideas and solutions usually becomes property of the organizing organisation and is used for their own benefit. The entries are usually invisible to other participants. An internal team of professionals mostly performs the evaluation and selection of the entries. Often, one or more winning entries receive a financial reward or credits on the crowdsourcing platform. This competitive element intends to be a stimulus for the participants to try as hard as they can and to come up with an idea that is as
Cooperative innovation processes require different intellectual property management systems than closed innovation systems. Therefore, new forms of intellectual property evaluation, monitoring, and management will emerge when the innovation process phases are influenced by crowdsourcing initiatives (Enkel, Gassmann & Chesbrough, 2009).
Data security
In order to be most efficient and effective in helping to resolve the problem, according to Gao, Wang, Barbier and Liu (2011) the members of the response group should subscribe to the centralized information management system to ensure data integrity, data security, accuracy, and authentication for each member of the response group. In hospitals this data security might be even harder because of the patient data. Halder (2014) mentions the privacy concern with the use of mobile-based crowdsourcing health services platforms that contain unencrypted patient data. Halder also states that contributors in any crowdsourcing initiative look for high level of privacy, security, anonymity and guarantee for data protection. This might also play a role in the performance of crowdsourcing on the innovation process of hospitals.
Advanced conceptual model
The researched information can be combined with figure 1 to advance the conceptual model with more detailed suggestions from the literature. This is reflected in figure 2.
Figure 2: conceptual model: the influence of the crowdsourcing process on the innovation phase(s) of hospitals including possible influencers and crowd of the innovation process.
Methodology
Design and scope
In order to map the phases and activities of the influence of crowdsourcing on the innovation process of Dutch hospitals, this study uses a multiple case-study design. Qualitative case study methodology provides tools for researchers to study complex phenomena within their contexts (Baxter & Jack, 2008). A case study is an empirical inquiry, which focus is on a contemporary phenomenon within its real-life context and the boundaries between phenomenon and its context are not clearly evident (Yin, 2013). Furthermore, Yin also states that a case study is suitable for studying complex social phenomena. A qualitative method that consists of semi-structured interviews with open questions will be conducted to gain augmented insights into the crowdsourcing opportunities for Dutch hospitals at external parties (e.g. technological vendors). Identifying various insights from different actors within
Crowdsourcing - Characteristics - Top-down/bottum-up - Information sharing - Intellectual property - Monitoring - Data security - Reimbursement strategy ? Idea generation
phase Research phase Development phase Commercialization phase
'Crowd' involved - research centres - consultants - universities ? Crowdsourcing - Characteristics - Top-down/bottum-up - Information sharing - Monitoring - Reimbursement strategy ? 'Crowd' involved - research centres - consultants - universities ? Crowdsourcing - Characteristics - Top-down/bottum-up - Information sharing - Monitoring - Implementation of rigorous processes ? Crowdsourcing - On the job training - Characteristics - Top-down/bottum-up - Information sharing - Implementation - Training - Monitoring ? 'Crowd' involved - technological vendors - material & component suppliers
?
'Crowd' involved - technological vendors - material & component suppliers
the clinical environment of academic and non-academic hospitals is considered essential to be able to answer the research question.
Respondents for the case study will be selected based on specialist that are involved in innovations within hospitals and on the relations of Royal Philips with relevant stakeholders such as hospitals and professionals in the clinical environment of the health care sector. These stakeholders are appropriate for this case study since they might be open for, or already work in, collaboration through crowdsourcing with hospitals. The selected Dutch hospitals are both academic and non academic. For further insides into the crowdsourcing possibilities there will also be responses from other professionals in the clinical environment of Dutch hospitals. This case can give a better inside into the need for innovation through crowdsourcing from Dutch hospitals and it can help mapping the specific phases where crowdsourcing initiatives are most applicable, which addresses the literature gap. Next to the Dutch specialists within hospitals, there was also an opportunity to talk to different experts of the clinical environment of hospitals in the US and the UK, these can give further insides on the clinical environment and the crowdsourcing opportunities for Dutch hospitals.
Data collection & sample
Information including the current theories about crowdsourcing, open innovation and the health care sector is collected from previous academic literature research and websites. This is in line with the triangulation theory, which assumes, that if two or more sources of data, or researchers converge on the same conclusion, the conclusion is more credible (Tracy, 2010). The field research is done through interviews with different actors from Dutch hospitals that are used as a case study for this research. Next to this, the needed information about the external crowdsourcing initiatives has been obtained from several individuals who have the knowledge of the specific clinical domain of hospitals (e.g. Royal Philips). The primary data is obtained through conducting in-depth interviews with actors involved in
innovation within academic and non-academic hospitals.
The covered topics are based on the characteristics that influence the innovation process in the health care sector, which could in turn be influential for the crowdsourcing process. The interviews take about one hour and are recorded with permission of the interviewee. Afterwards, the interviews are transcribed and coded on subject. Interviewing is a way to collect data as well as to gain knowledge from individuals (Kajornboon, 2005). As a result, from these data, an insight is given into how Dutch hospitals can use crowdsourcing in relation to the innovation process phases to innovate. In turn, this addresses the literature gap. The interviews assist the awareness of the innovation process within hospitals and the influence of crowdsourcing on this process. They help to describe the different phases of the innovation process and give an insight into the concept of crowdsourcing related to the innovation process in Dutch hospitals. To give further insights on the innovation process and the crowdsourcing concept, also experts from outside the Netherlands are included in this research. More detailed information about the interviewees can be found in figure 1. The interviews are transcribed and coded based on structure and concepts such as different phases that can be distinguished in the innovation process of hospitals and the collaboration opportunities with external partners.
Interviewee Domain Department Country Role HAGA1 Hospital Radiology &
Nuclear Medicine
Netherlands Specialist, department head, Dutch radiology board principal
HAGA2 Hospital ENT department Netherlands ENT specialists, department head
AMC1 Hospital Innovation
Exchange
Amsterdam (IXA)
Netherlands Innovation Manager
AMC2 Hospital +
Technological Vendor
Research Program Office
Netherlands Medical doctor in surgery
AMC3/ VUMC
Hospital Children Digestive system
Netherlands Medical doctor & research
UMCG1 Hospital Medical Oncology Netherlands Medical Specialist UMCG2 Hospital Innovation Lab Netherlands Innovation specialist
(research background) UMCG3 Hospital Innovation Lab Netherlands Innovation advisor
Wenckebach institute - UMCG
Philips1 Technological
Vendor Chief Office Medical United States Global Director Medical & Health Affairs Philips2 Technological Vendor Chief Technology Office United Kingdom Innovation Strategy Specialist Philips3 Technological Vendor Diagnoses and treatment United States
Chief scientific officer Figure 3: interviewees list
Strengths and limitations of the research design
This explanatory research could also be applicable for other organisations that are looking for ways to use external crowdsourcing to innovate. According to Noor (2008), explanatory research can be useful for example to study processes in companies. The model used is especially applicable for organisations that operate in the health care sector since the innovation process framework is based on hospitals. The questions and theories could be easily tested for other organisations that want to know where in the innovation process they should focus on to target the phases that are most relevant for crowdsourcing activities. The unit of analysis is a prototypical case (Pratt, 2009).
of these is lack of systematic conduct of data. Systematic reporting of the retrieved information could prevent this. Another criticism for case studies is that it is no basis for scientific generalization but instead the purpose of this kind of research is the generalisation of theoretical propositions. A last criticism mentioned by Yin is that case study design takes too long and that it ends up as an unreadable document. This could be prevented by make sure to structure the research well. To ensure internal validity, also conflicting literature is included in this research. By using multiple sources of evidence to build construct measures, this study can establish construct validity (Eisenhardt, 1989). Furthermore, it is important to discover the underlying theoretical reasons why a certain relationship between concepts exists. This helps to establish the internal validity of the findings (Eisenhardt).
Analyses Strategy
NVivo, version 11 is used for coding and analysing the data. According to Welsh (2002), NVivo can be used in the data analysis process. Computer assisted qualitative data analysis software (CAQDAS) can be helpful to the researcher in her or his search for a precise and clear view on the data whilst also providing an analysis of the data examination process in total, this is something that has often been lacking in qualitative research (Welsh, 2002). With the coding software, the data can be structured according to specific themes. According to Braun and Clarke (2006), thematic analysis should be seen as a primary method for qualitative analysis. They argue that it is the first qualitative method of analysis that researchers should acquire, as it provides core skills that will be useful for conducting manifold designs of qualitative analysis. Furthermore they explain that thematic analysis is a method for identifying, analysing, and reporting themes within data (Braun & Clarke). To create a broad overview of the themes that prominently came forward during the interviews a word map is acquired with NVivo (Appendix 1).
NVivo can either be free nodes that are autonomous with no clear coherent relation with other nodes or tree nodes that permit a ranked structure, moving from a generic category at the top, also called the parent node, to more definite categories, also called child nodes, below (Siccama & Penna). A node structure including parent and child nodes is used to structure the data, this structure can be found in Appendix 2.
Results
In this chapter the main findings from the interviews will be presented. The interview results will be structured in this section based on the conceptual model and additional findings. Two main findings topics resulted from analysing the interview data, in Appendix 3, a hierarchy chart from NVivo can be found which enhances the two main findings. Firstly, the influence of crowdsourcing activities on the innovation process phases of Dutch hospitals is described per phase including the main barriers. Furthermore, specific parties involved in the different phases of the innovation process of hospitals are mentioned.
Influence of crowdsourcing on the innovation process
In this section, the perspectives of the interviewees on the influence of the crowdsourcing activities on the innovation process phases of hospitals are given. To structure the findings, a clear distinction is made between the four different innovation phases based on the conceptual model.
Idea generation phase
For the idea generation phase of the innovation process of hospitals, the participants have described how the influences of crowdsourcing in this phase could occur, namely through collaboration, communication and events. Collaboration between parties is described most frequently by HAGA hospital, AMC and Philips. This could be collaboration with
technological vendors to come to new insights or collaboration with companies to see how they do things to generate ideas. With good collaboration, hospitals can come much further in their innovations states the medical doctor in surgery of the AMC:
"There is a initial phase, you have an idea for a product and if we collaborate we can take this product much further and we get into contract about confidentiality and non-disclosure and all these kind of stuff and then you can set out your plan on not only developing the product vs. bring it to a minimal viable product or bring it up to a trial and focus on making claims or an FDA process for instance (AMC2)."
This quote shows that collaboration is of considerable importance in the idea generation phase since here the contract can be set-up, which can be a good foundation for the next innovation process phases.
Next to collaboration, especially the interviewees from Philips and HAGA see communication as important since there has to be regular interaction between the parties to come to the best result. The medical specialist from HAGA hospital described:
"Sometimes one has an idea but there is too little exchange, so big data and big dating. The more we talk about what we want, the more we can reach (HAGA1)."
Communication helps to explore the intentions of the parties involved, when everyone knows what is expected, this will probably foster collaboration and in turn stimulate the innovation. Furthermore, events came forward during the interviews as influence of crowdsourcing specifically for the idea generation phase. User events with vendors is described as an event that could influence crowdsourcing on the innovation process, crowdsourcing can take place at user events where hospitals meet future partners. An example
“From the very first start, you can develop fantastic things but there has to be a specific request, is demand existing and are there possibilities in the technology? That comes down to the first phase. We look for companies with specific knowledge, within the clinical and research environment from the literature and parties we know from congresses. We meet new contacts at congresses, mostly department specific events. (AMC3/ VUMC).”
Price contests are innovative crowdsourcing events that are held to increase the input for new ideas on existing problems or issues that the hospitals want to solve.
“An example of something innovative lately was that the dermatology department needed
breathing material and there was a price contest from the AMC to come to new ideas related to a model. The technological university worked together with us to look if it could be implanted (AMC3/VUMC).”
Another example of an event to gather new ideas on a certain question that hospitals could have is organising health hackathons or marathons. The Innovation Lab of the UMCG organised such an event that can be explained by the following quote:
“Last weekend we organised hacking health together with four other university medical centres, […] and what we did there was invite people from inside the hospital, programmers, patients and entrepreneurs and creative professionals from outside the hospitals and join teams during one weekend. Problems where pitched on Friday and worked out during the weekend and Sunday we presented for a jury. This can be seen as an open call to colleagues in other hospitals (UMCG2).”
The aforementioned events foster innovation through crowdsourcing and impact the idea generation phase in particular since they are organised with the aim of increasing input for new ideas within the hospital by involving other parties.
Some interviewees described searching partners for insights, sourcing at other hospitals, validation of the idea, platforms, internal crowdsourcing and searching outside the hospital as part of the influence of crowdsourcing on the innovation process. Since these where mentioned by little of the participants, these influences are less striking and less grounded. The need for crowdsourcing activities for hospitals in the idea generation phase is emphasised by Philips.
"So these heads of the departments say, “Here is where we want to be.” and they went out and try to look at innovate solutions by looking outside of the environment and help to execute their idea (Philips1)."
Furthermore, although intellectual property is mentioned as a barrier to crowdsourcing for innovation in the health care sector, the interviewees also describe this as part of the influence of crowdsourcing on the innovation process.
"I think the protection of the idea is very complex to hospitals in general, it is hard to understand what it entails, meaning the idea protection (AMC2)."
When crowdsourcing for innovation, the intellectual property is a complex entity involved in the process. The descriptions of the participants give a more specific insight into the activities that appear during the crowdsourcing process involved in the idea generation phase. More detailed data about the characterization of the influence of crowdsourcing on the idea generation phase can be found in table 2 in appendix 5. Below, a summarised description of
Figure 4: a visualisation of the practical influence of crowdsourcing on the idea generation phase Research phase
The participants described diverse influences of crowdsourcing on the research phase. Therefore, a relevant selection of the insights from the data is made. The main influences in this phase are a collective database, administrative affairs and information sharing. A collective database is described as an influencer of the research phase, which can be a collective database of different hospitals, different organisations or even an international database.
"In the Netherlands we have for example a database to collect all data of a specific tumour type. In Europe we are part of European association the ENET, the European society that for example provides data needed or when a study is initiated then it is done via the European community (UMCG1)."
Here the UMCG uses a database to collect data or information that is needed when initiating a study or doing research. Another example of a collective place to crowd source is a platform to interact with researchers. This can also be a platform among different parties, for instance a crowdsourcing activity between the hospital and a technological vendor as described by a medical specialist at the AMC:
Crowdsourcing Idea generation
phase Research phase Development phase Commercialization phase
Collaboration Communication
Events
Intellectual property Barrier:
"We had ten specialists throughout the AMC that participated on a platform to interact with researchers on silence. Because of all the IP and confidentially issues this was a platform that Philips choose, a SharePoint platform (AMC2)."
Secondly, administrative affairs e.g. contracts, licencing and intellectual property, is described as influence of crowdsourcing activities on the research phase. Intellectual property is also mentioned for the idea generation phase. Thus, these administrative affairs can sometimes even overlap.
"Every specific agreement that we make will use terms and condition of the master research agreement so the intellectual property rights, how the project is monitored, how the project started, what documentation is needed (Philips2)."
This quote stresses out the importance of setting up a contract or agreement in the research phase since this has influence on the future perspective of the project. Furthermore, according to the innovation manager at the AMC: “Contacting third parties is the next step after the idea generation”. When the problem is clear, hospitals can start searching for external parties that can help to realize the idea (AMC1).
Lastly, information sharing is inevitable when crowdsourcing in the research phase, other parties need access to the information and data.
"I give information about how the process should go. With open connections, this company can make a connection with the information systems of our hospitals (HAGA1).”
When hospitals want external parties to help with the technological fit, information sharing is also important to get the right technology corresponding with the actual idea. Moreover,
and structuring of data and for getting the right research report. The more accurate the information, the better the information report. This statement is supported with a quote from the medical specialists of the HAGA hospital.
"I’m now in contact with a new compliance group who make dashboards for operating rooms [...]. On the operation rooms they can see how often the door closes and opens and the risks at infections and you can compare the patients under anaesthesia. How fast will the report about the patient be ready and how soon is the doctor informed (HAGA1)."
Moreover, the data security should be taken into account when sharing information. The participants most frequently see data security as a barrier for crowdsourcing in the health care environment of Dutch hospitals as the AMC, HAGA and Philips describe it. The patient safety issue is here the underlying problem that prevents hospitals to openly share data about their ideas or problems in an open system. As stated by a department head of the HAGA hospital:
"The patient safety issue is a barrier, you cannot send photos through Whatsapp, this should all go through safety channels. The systems are not open and they are not connected (HAGA1)."
Because of privacy regulations hospitals have to make sure that the data cannot be traced back to specific patients, this makes it hard to share patient data with other parties.
“For us for privacy of data we need to follow specific protocols and we cannot send specific information about the names of children and this is strict. Protocols need to be approved by the medical committees. This can be a barrier, and lot of paperwork, but there is no other way (AMC3/ VUMC).”
This quote indicates that data security is a barrier for crowdsourcing to come to innovation but it also indicated that this barrier could lead to more administration work. In contradiction, UMCG does not mention data security as a barrier, they acknowledge it but see it as a must to ensure the patient safety as seen in the quote of an innovation specialist of the UMCG.
“On innovation, well of course all kinds of data security and compliance to those rules […] What I know now is that it is good that the regulations are there and we are dealing with patient health care, so safety comes first (UMCG2).”
A structured table with a description of the influences and corresponding quotes of the crowdsourcing process on the research phase of the innovation process of Dutch hospitals can be found in Appendix 5, table 3. In figure 5 a visualisation of the descriptions of the influence of crowdsourcing on the research phase is showed.
Figure 5: a visualisation of the practical influence of crowdsourcing on the research phase Development phase
The participants describe the influence of crowdsourcing on the development phase of the innovation process of hospitals in terms of collaboration, communication and administrative
Idea generation
phase Research phase Development phase Commercialization phase
Crowdsourcing Collective database (platform) Administrative affairs Information sharing Data security Barrier:
