Crowdfunding: The effects of backer involvement on the crowdfunded product

Crowdfunding: The effects of backer involvement on

the crowdfunded product

Dual Award Master

Advanced International Business Management and Marketing

By

Sophie van Poele

University of Groningen: S2529580

Newcastle University Business School: B140674635

Supervisors:

University of Groningen, Faculty of Economics and Business: Dr. Bartjan Pennink

Newcastle University Business School: Dr. Hanna Bahemia

Abstract:

This research aims to gain insight into the effect of backer involvement on a crowdfunded product. Existing literature on product co-creation and crowdsourcing indicate that backer involvement in the new product development process of a crowdfunded project might be beneficial to the resulting product. This resulted in two hypotheses measuring the impact of using the backer as an information source or co-creator on the innovativeness of the resulting product, and two measuring the impact of the same variables on product advantage. After the collection of data through a non-probabilistic sample of Kickstarter projects, the results were analysed using linear regression. For three hypotheses, no significant effect was found, while the influence of using backers as co-creators yielded a significant negative effect. These surprising results contribute to the small but growing academic literature on crowdfunding. This is one of the first studies that empirically and quantitatively tests relationships that occur in crowdfunding, a new and fast-growing financing alternative. With these results, the research attempts to close the gap in academic literature concerning the role of backers on the new product development, while also shedding light on what happens to a crowdfunded project after its campaign has ended. For entrepreneurs running crowdfunding campaigns, these findings might provide additional insight in, and help shape expectations of, their relationship with backers.

Acknowledgements:

Table of contents

1.3 Research question and rationale ... 8

1.4 Research design ... 10

1.5 Structure of thesis ... 10

2. Literature review and conceptual development ... 11

2.1 Introduction ... 11

2.2 Crowdfunding – A definition ... 11

2.3 Differences between crowdfunding and other sources of finance ... 13

2.4 Reasons to crowdfund ... 15 2.5 Crowd participation ... 16 2.6 Critique on crowdfunding ... 18 2.7 Theoretical lens ... 19 2.8 Hypothesis development ... 22 2.9 Measurements ... 28 2.10 Sample ... 29 2.11 Conclusion ... 30 3. Methodology ... 31 3.1 Introduction ... 31 3.2 Research paradigm ... 31

3.3 Primary data collection instrument ... 32

3.4 Ethical considerations ... 33

4. Results ... 36

4.1 Introduction ... 36

4.2 Preliminary data analysis ... 36

4.4 Conclusion ... 42 5. Discussion ... 43 5.1 Introduction ... 43 5.2 Discussion of results ... 43 5.3 Managerial implications ... 46 5.4 Theoretical implications ... 46

5.5 Limitations and suggestions for future research ... 47

1. Introduction!

Since the 2008 financial crisis, it has become increasingly difficult for companies to secure company finance through traditional means (Cosh, Cumming, and Hughes, 2009, Calveri and Esposito, 2013). In the U.S., the year 2009 had the largest decline in loans to private individuals since 1942 (Calveri and Esposito, 2013). Although venture capitalists suffer less of an information asymmetry when compared to banks, and are therefore more likely to fund riskier companies and projects, even their funding for innovative projects has declined in recent years; as many as 95% of proposals from aspiring entrepreneurs is rejected (Calveri and Esposito, 2013). Cosh et al. (2009) find that venture capitalists provide firms with only 4% or less of their desired capital when they have recently developed an innovation, and stage their payments to mitigate agency costs and information asymmetries. Bhide (1992) shows that venture capitalists receive 60% of their profits from only 7% of their portfolio, while 30% of their portfolio yields nothing. Therefore, every project that venture capitalists back must be a ‘potential home run’. Innovative start-ups are an especially risky investment because of the lack of business experience and credentials their owners often possess, and the lack of collateral to offer against the investment. This is enhanced by the fact that many start-ups target niche markets, thrive in rapidly-changing markets, or are based on me-too strategies. (Bhide, 1992, Dushnitsky, 2010).

chapter provides a background to the study, before introducing the purpose of the study and the research question, and concludes by highlighting the gaps in the literature that this research intends to address.

1.2 Background

At present, crowdfunding might seem an insignificant source of capital to the untrained eye. However, crowdfunding as a means of financing is rapidly growing, and is poised to become a significant way of financing in the future (Mollick, 2014). For example, in March 2014, U.S.-based crowdfunding platform Kickstarter surpassed the $1billion-mark in terms of pledges made, and stood at over $2,1 billion on December 2, 2015. In 2014, approximately $60,000 was raised every hour through crowdfunding worldwide (Self, 2014). In the second quarter of 2014, 393 new crowdfunding projects were started per day, receiving an average of 25,560 pledges daily between them (Crowddatacentre, 2015). In 2014 41,3% of all products funded was business and entrepreneurship-related, with the rest being mainly philanthropic or creative projects (Massolution, 2015). Crowdfunding appears especially popular with products related to technology and gaming and those concerning films and design. These categories received respectively 706,000 and 500,000 pledges over Q2, 2014. (Crowddatacentre, 2015). Reward-based crowdfunding received $2,097,939 of funding per day over 2014, amounting to more than $190 million that year, or a growth rate of 84% (Crowddatacentre, 2015).

activity. Angel investor networks in Kenya are rare or non-existent, and crowdfunding fits perfectly in the local culture. Thus, the crowdfunding movement in Kenya expanded rapidly, and the country became home to Babandu and M-Changa, the two largest African crowdfunding sites. Significant crowdfunding activity in Africa is also visible in South Africa and Nigeria (Schroter, 2014).

In conclusion, numbers show that the practice of crowdfunding is rapidly growing worldwide, becoming a more mainstream method to finance a project, product or venture. As it is based on ‘crowd’ contributions, crowdfunding engages a far greater number of individuals in financing an idea or product than the traditional methods of financing through banks or investors (Mollick, 2014). Moreover, both people that run a crowdfunding campaign (hereafter: entrepreneurs) and the members of the crowd that contribute money (hereafter: backers) start or contribute to a crowdfunding project for diverse reasons, as elaborated upon in chapter 2. Crowdfunding also offers entrepreneurs and backers a much more direct method to communicate compared to traditional methods of financing, oftentimes facilitated by the crowdfunding platform through which the campaign is run. This makes direct backer feedback on the project possible (Kuppuswamy and Bayus, 2013). The combination of a fairly new concept of finance that enjoys explosive growth in combination with the increased communication between the diverse individuals that are engaged in it, makes for interesting research on the products that result from such a collaboration. The results from this study can be used both in academic research as a subset of literature on crowdsourcing and product co-creation, and in practice by entrepreneurs that consider a crowdfunding campaign.

1.3 Research question and rationale

and presents highly varied results. This gap is also mentioned by Cumming et al. (2015) and Mollick and Kuppuswamy (2014). The second type of research gap concerns the backers of a project. Belleflamme et al. (2014) note that more research is necessary on the differences between crowdfunding initiatives that allow their backers to participate in decisions about product development and/or have voting rights on strategic decisions, and crowdfunding initiatives that do not grant their backers these powers. Gerber et al. (2013) find that entrepreneurs learn from their relationships with backers, which they appreciate for their role in improving and validating the product, but the exact results of this collaboration are currently unknown. Gerber et al. (2013) and Belleflamme et al. (2014) therefore advise more research on the roles of backers, observers, and entrepreneurs. This research aims to address both types of gaps in the literature, in an effort to enhance understanding and contribute to the academic literature concerning this topic, as well as providing practical information and advice to entrepreneurs that start future crowdfunding campaigns. The main research objective is then:

The main research objective is to understand the influence of non-monetary backer involvement on the final product that results from a crowdfunding campaign.

With this research objective in mind, the first gap in the literature is addressed through researching the impact of backer influence during the last stages of the new product development process on the final product when it starts the product life cycle. The second gap in the literature is addressed by looking specifically at non-monetary backer involvement; i.e. whether idea sharing, beta-testing, feedback, or any other form of involvement has an influence on the final product that results from the crowdfunding campaign. These two aspects of the research objective are addressed by answering the following research questions:

1. What is the influence of non-monetary backer involvement on the final product that results from a crowdfunding campaign?

1.a What is the influence of non-monetary backer involvement on the innovativeness of the final product that results from a crowdfunding campaign?

1.4 Research Design

These research questions are answered through various means. Initially, academic literature is reviewed in order to lay the theoretical foundation for this research. From academic literature on crowdfunding, customer co-creation of value, new product development, and various other topics, definitions for constructs are taken and the relationships among them investigated. Taking previous research into account, the decision is made for an objectivist stance and a post-positive theoretical position for this research, where the assumption is made that observable phenomena underlie theoretical constructs. As a result, primary data collection is executed through an online questionnaire, which consists of constructs and survey items taken from previous research. The sample used is based on a convenience sampling selection method, as the entire population is too scattered and inaccessible to target through other means. The results of the data collection, which are quite surprising, are presented thereafter, along with a discussion, managerial and theoretical implications, and suggestions for future research.

1.5 Structure of thesis

2. Literature Review and Conceptual Development

In this chapter, literature concerning crowdfunding is critically reviewed. The theoretical concepts and relationships required to address the research question are introduced, upon which the conceptual model and hypotheses can be built. After the introduction of the hypotheses, the choice for measurements and sample is elaborated upon.

2.2 Crowdfunding – A definition.

raising money for politics or an individual (Wroldsen, 2013), internet peer-to-peer based lending (Lin and Viswanathan, 2013, Calveri and Esposito, 2013), or fan-based fundraising for a music group or art form (Burkett, 2011 in Mollick, 2014). For this research, only crowdfunding project are included that comply with the definition given in this paragraph, as only projects whose creators are seeking monetary rather than intellectual contributions and whose backers actively seek a reward for their investment can be viewed as financing projects rather than funding or donation-based projects (Gerber et al., 2013).

launch stage, and are proceeding to the introduction stage of the product life cycle (PLC). This defines the product phases on which this research focuses, which is relevant to bridge the first gap in the literature concerning the crowdfunded product’s transition between the new product development process and the start of the PLC.

2.3 Differences between crowdfunding and other sources of finance

Several large differences can be observed between crowdfunding and other sources of finance, most of which are related to the much greater amount of individuals that are engaged with one project/product, and the relationship of the entrepreneur with them. Firstly, as backers that fund a project have proven to be interested in that product, crowdfunding can not only be used to secure funds, but also to demonstrate the demand for the proposed product (Mollick, 2014). For entrepreneurs, this can be a form of validation and encouragement to proceed with the project (Gerber et al., 2013). Moreover, when demand for a product has been demonstrated, entrepreneurs may proceed to secure funding from more traditional sources, as did the creators of the Pebble Smartwatch (Dingman, 2013). If the crowdfund action proves unsuccessful, the project can also be abandoned or altered. Another benefit of running a crowdfunding campaign is that securing funds and exposure to potential customers are done simultaneously. The press sometimes follows crowdfunding campaigns, and may provide the entrepreneur with free publicity, as happened with many highly successful Kickstarter campaigns such as the Coolest Cooler and Pebble Smartwatch (Coolest, 2015, Pebble Technology, 2015, Scholz, 2015). This leads to a greater product/brand awareness and recognition in potential customers, which is important especially if the project comes with complementary products, such as game consoles and games (Mollick, 2014, Dingman, 2013).

hold no shares and often do not have experience as an entrepreneur themselves. This means that the opinion of backers can vary in usefulness to the entrepreneur, and that the entrepreneur is not obliged to take the opinion of backers into account. Furthermore, the relationship between entrepreneurs and backers differs from tradition because the funding is provided by a vast amount of small contributors instead of the traditional few investors with large contributions (Kuppuswamy and Bayus, 2013). This diminishes the importance and strength of voice of each individual contributor. In this regard, the power structure of the group of contributors resembles a pluralist diffusion of power, where power is fragmented amongst many, rather than an elitist diffusion of power, where a few wealthy investors are in charge (Barry, 2013).

diminished when the end of the funding period draws closer, due to extra exposure and updates from the entrepreneur and the relative inertia in the middle of the funding campaign (Kuppuswamy and Bayus, 2013). Lastly, because the contribution of individual backers and the risk of the investment are so low, especially in an All-or-Nothing format, it is less necessary for backers to monitor and assess the progress of the company than in traditional ways of financing, reducing risk for both the company and the backer (Agrawal et al., 2015).

Finally, some differences are not related to the amount of, or relationship between, backers and entrepreneurs. An example of this is that laws and official regulations concerning crowdfunding are incomplete for both backers and entrepreneurs, because of the phenomenon’s relative newness (Mollick, 2014). This stands in sharp contrast with the regulated business of purchasing shares or granting loans. This lack of regulations might incur fraud, but can also be a source of flexibility. Bhide (1992) notes that entrepreneurs that do not sell a majority stake to large investors retain strategic flexibility that is sometimes essential to make a business profitable. Additionally, Calveri and Esposito (2013) and De Buysere et al (2012) note that the fact that entrepreneurs might secure funding from another source than banks and investors might have positive effect on the financial sector as a whole, potentially reducing risk and fraud through increased competition and transparency.

2.4 Reasons to crowdfund

Reasons for backers to fund a project are varied and complex. Backers might find the project important, and want to see it succeed. Others want to personally support the founders, make a political statement, or find contributing to a project entertaining (Mollick, 2014). Backers of the more charity-based forms of crowdfunding might be motivated by principles of reciprocity (Calveri and Esposito, 2013). Many backers are not only financially motivated, but use the crowdfunding campaign to e.g. learn new things or expand their network (Schwienbacher and Larralde, 2010). Gerber et al (2013) find that backers like the idea of ‘creating value’ without needing too much investment or large corporations, and receiving a reward in return. Additionally, backers contribute because they want to be associated with, or be part of, a project that they would otherwise not be able to be involved in (Gerber et al., 2013, Schwienbacher and Larralde, 2010). In addition, ‘community benefits’, or the additional, private benefits that backers receive through their participation in the project, are an important reason for backers to contribute (Gerber et al, 2013, Belleflamme et al., 2014, DeWit, 2012). Community benefits make backers feel like a ‘special group’, as they often enjoy privileges that others do not, such as having earlier access to a product, receiving a special product (e.g. a customised version of the product), a material reward, or a token of appreciation (e.g. a project t-shirt), having preferential access to the entrepreneur through direct communication, or being among the people allowed to make suggestions or vote on aspects of the product (Belleflamme and Lambert, 2012, Belleflamme et al., 2014, Gerber et al., 2013). Community benefits that backers experience while backing a project increase when backers engage with the project or have an influence on the development of the final product, for example in terms of the colour or specific capabilities of the final product, while the opinions of the crowd can also have a significant influence on strategic decisions in the early stage of the business (Belleflamme et al., 2014, Belleflamme and Lambert, 2012, Gerber et al., 2013). These increased community benefits are not only an indication of why backers decide to contribute financially to a crowdfunding project, but also why they subsequently want to engage in the project and communicate with other backers and the entrepreneur. The next section elaborates on this matter.

2.5 Crowd participation

from co-creation and crowdsourcing. From approximately the 1970’s onwards, the business paradigm of active businesses that fulfilled the needs of passive consumers has diminished in importance (Kleemann et al, 2008, Pralahad and Ramaswamy, 2000). Increasingly, the relationship between consumers and companies became reciprocal, with the consumer becoming active and involved in the actions of the company, sometimes even aiding the company in its new product development process (Skaržauskaitė, 2013, Cui and Wu, 2015, Von Hippel and Katz, 2002, Kleemann et al., 2008, Hoyer et al., 2010). Many companies have already encountered or reaped the benefits of this phenomenon in the business world, e.g. Dell and its IdeaStorm community, Starbucks’ MyStarbuckIdea platform, and SAP and Microsoft’s invitation for customers to engage in brainstorms and discussions on new applications, and numerous other examples (Bayus, 2013, Sigala, 2012, Nambisan and Baron, 2009, Ramaswamy and Gouillart, 2010). In these projects, the specific roles that were fulfilled differed, but the similarities are that a large group of customers that were no employees of the firm provided their input or perform tasks for the company without monetary compensation, and this delivered desirable results (Kleemann et al., 2008, Hoyer et al., 2010). The number of firms engaging in crowdsourcing, one type of customer involvement, grew 53% in 2009, and 74% in 2010, yielding over 100 million dollars in the US that year (Frankrone, 2013).

value can take place in various stages of the production process. However, for this research, the co-creation activities performed during the last stages of the NPD process are most relevant. Grönroos (2008) and Payne et al. (2008) show that in the creation process, the co-creating customer and the company create value together as equals, with both parties benefitting from the results.

An example of crowd involvement is given by e.g Surowiecki (2004). He describes instances of crowds producing successful answers to all types of problems, be they cognitive (a problem with a definite solution), coordination (trying to coordinate behaviour in a group where everybody tries so too), or cooperation problems (having disinterested people collaborate). He also asserts that any crowd is not always right, but that the larger the group, the greater the chance that their collective answer will prove (near) correct and/or valuable (Surowiecki, 2004). For the wisdom of the crowd to be effective and the crowd's judgment to be accurate, the crowd should possess four characteristics: (1) "diversity of opinion," (2) "independence," (3) "decentralization," and (4) a mechanism for aggregating individual judgments.' (Surowiecki, 2004). In crowdsourcing and co-creation, the first and third characteristics that Surowiecki (2004) proposes are fulfilled, as every member of the crowd will have a different opinion, and their large geographical disparity will ensure independence. The second characteristic is more or less fulfilled, as members of the crowd will make an individual decision or suggestion, but this might be influenced by the actions of other contributors and herd mentality (Agrawal et al., 2011). Usually, an online mechanism for aggregating information or judgements is in place (Sigismund Huff et al., 2013). As with all knowledge, crowd involvement is only beneficial to the final product if the company producing it is able to distil and connect the relevant knowledge from all information they receive, and successfully apply it to commercial ends (Jansen et al., 2005)

2.6 Critique on crowdfunding

first and contribute the most, thereby building trust and setting examples for other backers. The effect of this ‘herding behaviour’ is also discussed by Kuppuswamy and Bayus (2013), who mention that the visible activities of backers might induce non-rational behaviour in other backers. This phenomenon has also been observed in the choices that people make in downloading music or bidding on online auctions, with more downloads or bids for the items that were popular rather than those that provided quality to the consumer (Kuppuswamy and Bayus, 2013). Therefore, projects might succeed on the basis of the entrepreneurs’ social capital rather than the quality of his/her idea. Further critique concerns the purpose of crowdfunding, as for some entrepreneurs, crowdfunding is a means to market their product and provide an indication for the demand for a product, rather than a financing method (Lambert and Schwienbacher, 2010, Schwienbacher and Larralde, 2010, Scholz, 2015).

In addition, being successfully funded during a crowdfunding campaign does not mean that the product or company will develop accordingly. Mollick (2014) shows that many successfully funded projects are seriously delayed in their development and delivery, with only 24,9% of projects delivering on time, and the others experiencing an average delay of 1.8 to 2.4 months. This can be due to overfunding, where the company is unexpectedly overwhelmed with funding and requests for their product, and strain their supply chain (Mollick, 2014). Also, interdependencies may cause delays, as the entire project can be delayed when one part is late. Lastly, reward-based crowdfunding takes place when the new product development stage of the product has not yet ended. When changes in products or circumstances occur at a later stage, already established pledges may prove inadequate and/or remain unfulfilled (Mollick, 2014). Furthermore, high transaction costs are involved for start-in managstart-ing relations with many backers, the large amount of specific and sensitive company information they need to disclose to many relatively anonymous backers, and the absence of advice and guidance that can be provided by an experienced investor (Wroldsen, 2013, Duschnitsky, 2010). However, through reward-based crowdfunding, the control of the company stays in the hands of the entrepreneurs rather than in those of large investors, retaining a certain degree of long-term strategic flexibility (Wroldsen, 2013).

2.7 Theoretical lens – Relational View of the firm

the Porter Diamond and the resource-based view of the firm. They argued that while these two theories focus solely on finding the source of firm competitive advantage within the firm itself, critical firm resources might also be found outside firm boundaries, mainly from the relationships that firms have with others. When Dyer and Singh wrote their article in 1998, their focus and main unit of analysis were interfirm relationships. However, as noted in the literature review, customers that actively collaborate with the firm in order to create value can also be seen as a collective group with which the firm engages in a relationship that creates mutual benefits (Pralahad and Ramaswamy, 2000, Kleemann et al., 2008, Von Hippel, 2012, Skaržauskaitė, 2013). These benefits, or ‘relational rents’, are defined as “supernormal profits that cannot be generated by either firm in isolation and can only be created through the joint idiosyncratic contributions of the specific alliance partners” (Dyer and Singh, 1998, p. 662). The fact that the relationship with this group of non-employees is not a standard ‘arm’s length’ market relationship and can yield relational rents, can be proven when examining the categories that Dyer and Singh (1998) propose for competitively advantageous relationships:

1. Investment in relation-specific assets. Site specificity is not applicable here as the online nature of contemporary crowdfunding and crowdsourcing/co-creation blurs geographical limitations (Agrawal et al., 2011, Belleflamme and Lambert, 2012). Physical asset specificity, or tailoring activities to one specific partner, is not applicable as the crowd consists of many individuals, and their contribution is intellectual or monetary rather than physical (Surowiecki, 2004). Human asset specificity occurs over time, which is not applicable here as the collaboration lasts for a specific project only.

absorptive capacity, i.e. their ability to successfully identify, collect and apply their knowledge for commercial purposes (Jansen et al., 2005)

3. The combination of complementary, but scarce, resources or capabilities (typically through multiple functional interfaces), which results in the joint creation of unique new products, services, or technologies. The literature on crowdsourcing and co-creation shows that the involvement of seemingly random people or customers can lead to a very positive result in terms of idea creation, problem solving, information gathering and value creation, as has been described in the literature review (Surowiecki, 2004, Von Hippel, 2004, Ramaswamy and Gouillart, 2010, Mollick, 2014, Belleflamme et al., 2014, Schweitzer et al., 2014, Bayus, 2013)

4. Lower transaction costs than competitor alliances, owing to more effective governance mechanisms. Effective governance of the relationship is defined by Dyer and Singh (1998) as comprising of two factors: the ability to self-enforce rather than employing third-party enforcement mechanisms, and the ability to employ informal versus formal enforcement methods. As the collaboration between the crowd and the entrepreneur is in essence voluntary, self-enforcement must be present as formal enforcement mechanisms cannot be put in place (e.g. contracts between the crowd and the firm are not feasible). Additionally, as people are contributing their personal time and money, it is evident that informal methods must be in place, as formal ones (e.g. financial or investment hostages) are impossible in this type of relationship.

2.8 Hypotheses development

example, Pralahad and Ramaswamy (2000) point out that the locus of firm core competence is shifting from the single firm towards an ‘enhanced network’ consisting of the firm, the buyer/supplier network, and the customer. The incorporation of customer input has a generally positive effect on new product development success, as proven by Henard and Syzmanski (2001) in their metastudy. Products created with potential customers increases the likelihood that the product fulfils customers’ needs better or in a more efficient way than products created through a traditional NPD process, thereby increasing NPD succes (Ramaswamy and Gouillart, 2010, Ramaswamy and Ozcan, 2014, Hoyer et al., 2010 Pralahad and Ramaswamy, 2004). Lastly, qualitative research on the engagement of backers in a crowdfunding project show that this could aid in product success, as backers can pre-select, validate and contribute to the most innovative projects (Scholz, 2015).

all this, the following conceptual model was developed in order to answer the research questions discussed in chapter 1:

Figure 2.1 – Conceptual Model

practice of co-creation, as was discussed in the literature review, and connected to Dyer and Singh’s (1998) third possible source of relational rents: the combination of complementary and scarce resources and capabilities. It means that customers actively participate in the development process, thereby performing tasks for the entrepreneur, such as solving problems or beta-testing the product. As these consumer roles are so different, and their different effects on various constructs (e.g. product innovativeness) has been proven, they are also taken separately in this research.

The first hypothesis thus concerns relational rents in the form of new product innovativeness. Product innovativeness is here defined according to Lee and O’Connor’s research (2003) as the extent to which “the product’s technology, benefits, and features differ from other products of the same product category” (Gruner et al., 2014, p 34). In addition to the rationale for researching product innovativeness described above, developing innovative products is important for many companies in order to stay profitable, and is therefore relevant to research (McNally et al, 2010, Von Hippel, 2004, Fang, 2008, Chandy and Tellis, 2000). However, the relationship between customer involvement and product innovativeness itself is complex and in some ways contradictory, as some authors find a positive effect of including customers’ input into the NPD process, such as Franke et al., (2006), and some find a neutral or even negative effect, such as Menguc et al., (2014). As explained in the introduction, entrepreneurs with radically innovative products will turn to crowdfunding sooner than those with incrementally innovative products, because of the increased difficulty they have in securing traditional funds. In order to avoid confusion and measure the most appropriate relationships, the expected relationships concerning innovativeness formulated in these hypotheses are thus based on the influence of backer involvement on radically innovative crowdfunding projects in the last part of the NPD process. While overall negative impacts are found for involving customers in the early NPD stages of radical innovation (see overview by Menguc et al., 2014), customer involvement in the later stages of the NPD process in crowdfunding projects are likely to aid the innovativeness of the final product. Scholz (2015) shows that during these stages, a crowdfunded product needs to be “tested, further developed and validated” (p.15), which is facilitated with the help of backers. Backers not only pre-select the most innovative projects to fund, but also provide feedback to help improve the product further (Scholz, 2015). This is possible through providing the entrepreneur with “need and context-of-use information”, which is only generated by customers and is hard to obtain for companies because of its tacit nature (Von Hippel, 2004, p. 8). Thus, the relationship between backer input and product innovativeness is formulated as follows:

H1a: The involvement of backers of a crowdfunding project as an information source (CI) has a positive effect on the innovativeness of the resulting product.

Product advantage, or “superiority and/or differentiation over competitive offerings” (Henard and Syzmanski, 2001, p. 364) is one of the other constructs through which relational rents can be made visible. The difference between product advantage and product innovativeness is pointed out by Rijsdijk et al. (2010, p. 34), who note that “the innovativeness of a new product does not by definition imply that a product is meaningful to customers or superior to competing offerings”. Product advantage is thus an indicator of how well the company meets customer needs. Besides the importance of product advantage as a driver of product success, it is a relevant measure for two reasons (Song and Parry, 1997, Henard and Syzmanski, 2001). First, customers that engage in the NPD process transmit information to the company about their preferences and needs concerning a product. When this knowledge is correctly incorporated in the new product by the developing company, the final product fulfils the customers’ needs more fully or in a more efficient way compared to other products, making the product both superior and more desirable to other customers (Pralahad and Ramaswamy, 2004, Ramaswamy and Gouillart, 2010, Ramaswamy and Ozcan, 2014, Nambisan and Baron, 2009). Secondly, Veryzer (1998a) notes that customers can have considerable difficulties adapting to radically new products because of their lack of familiarity with them and the learning required to use them. Involving customers in the final stages of the NPD process can breed familiarity with the product and allows backers to make suggestions to the product in order to mitigate adaption difficulties, as happened with the Nike+ and Local Motors case studies in Ramaswamy and Ozcan (2014). Nambisan and Baron (2009) show that the occurrence of the above is possible though online customer involvement. For these reasons, the hypotheses concerning product advantage are formulated as follows:

H2a: The involvement of backers of a crowdfunding project as an information source (CI) has a positive effect on product advantage.

H2b: The involvement of backers of a crowdfunding project as co-developers (CC) has a positive effect on product advantage.

Control variable 1: Absorptive capacity. This variable is included in many experiments for product innovativeness and product advantage, sometimes with a different label. It is defined the capability to “recognize new external knowledge, assimilate it, and apply it to commercial ends” (Jansen et al., 2005, p. 3), and controls for e.g. the misappropriation of customer knowledge. The measure is relevant both theoretically, as Dyer and Singh (1998) argue that the absorptive capacity of the firm in relation to information given to it is a prerequisite for the generation of relational rents, and practically, as the exchange of knowledge between customer and entrepreneur is futile if the latter cannot process or apply it (Jansen, van den Bosch and Volwerda, 2005). Cohen and Levinthal (1990) note that the absorptive capability of the entrepreneur’s new product development team is more than the sum of each individual member’s absorptive capacity, due to interaction and communication with sources inside or outside of the firm. As the type of absorptive capacity that directly impacts the relationships mentioned in the hypotheses is that of the team, this level is appropriate here.

Control variable 2: R&D Intensity. This variable measures the absolute and comparative investment in its resource and development. Li and Cantalone (1998) show that this construct directly and positively impacts product advantage. Day (1994) considers R&D intensity an important base for new product development. It is hypothesised to be a moderating variable on the relationship between backer input and product advantage and innovativeness, because extra resources and investment in the new product’s development process can technically enable the collection and implementation of customer input. Where absorptive capacity controls for whether the project team is theoretically able to recognise and incorporate new knowledge received from customers, R&D intensity checks whether the team is enabled to do so in terms of resource allocation. Thus, this level is appropriate. Other scholars controlling for R&D intensity in the same context are e.g. Cui and Wu (2015).

this research (Day and Wensley, 1983). In order to ensure that the measured effect in product innovativeness and product advantage is caused by the incorporation of customer input rather than competitor imitation, this measure is included.

2.9 Measurements

In order to effectively measure the constructs described in the conceptual model, using correct and reliable measurement instruments is essential (Saunders et al., 2012). Thus, survey questions and items to measure the constructs were taken from published studies, in which they were tested and proven to be reliable and valid (Saunders et al., 2012). In order to research the two types of backer involvement reliably, the operationalisations and items of Cui and Wu (2015) are used. As mentioned in the previous section, they distinguish two relevant types of customer involvement, which captures the wide range of observed backer engagement methods in practice appropriately. Cui and Wu’s (2015) measures are especially suitable for this research, as they have been developed for companies that are engaged in innovative new product development, as are the companies from this research’s sample. Also their Cronbach’s alpha values proved their reliability (α=0,89 and α=0,90). Scholars such as Fang (2008), Gruner et al. (2014) and Langerak et al. (2004), and others have tried and tested various scales and operationalisations while measuring product advantage and product innovativeness. The selection for this research was based on the measurements’ scope, reliability in previous research, and similarities in terms of sample. Product innovativeness measures were taken from Gruner et al., (2014) for their (α = 0,91) reliability and their appropriate sample of producers of consumer durable goods. Product advantage measures from Langerak et al. (2004) were reliable (α = 0,73), reverse-coded, which reduces acquiescence bias in the respondent, and measured all aspects of the construct. Jansen et al.’s (2005) measures for absorptive capacity were adopted for their reliability (α = 0,71) and specificity of measurement. Li and Cantalone’s (1998) measures were taken for R&D intensity and competitor knowledge as for their reliability (α = 0,71 and α = 0,95, respectively). The final questionnaire that is used in this research can be found in chapter 3.

2.10 Sample

influencing variables concerning possible audience and method of presentation. In terms of platforms, Kickstarter is suitable for this research as it is one of the largest and oldest non-themed crowdfunding platforms (Kickstarter, 2015e). As Kickstarter only displays projects and excludes e.g. charity fundraising and crowdfunding personal expenses, Kickstarter has “become synonymous for reward-based crowdfunding” (Briggman, 2015), and is thus deemed a valid representative platform for reward-based crowdfunding projects in general. Additionally, Kickstarter conforms to all other prerequisites for a sample platform as described in chapter 2. Kickstarter is based on an All-or-Nothing principle, the advantages of which are elaborated upon in chapter 2 (Cumming et al., 2015). With a combined amount of $2 billion pledged, the average pledge being $70 and the mode $25, the ‘crowd’ of potential backers is sufficiently large (Kickstarter, 2015a, Kickstarter, 2015b). As backers and entrepreneurs from all over the world can start and back projects, no geographical constraints are present. Lastly, backer involvement is promoted by Kickstarter itself through their blog and in their ‘creator handbook’, a set of tips and guidelines for aspiring entrepreneurs (Orlando, 2015, DeWitt, 2015, Kickstarter, 2015c). On Kickstarter, the “technology” category was selected. This type of projects often delivers a tangible product that backers can realistically and objectively contribute to. Arts-inspired projects do not lend themselves to the purpose of this research for two reasons. First, the choice to back an art project is more influenced by personal taste than the choice to back a technology-type project, where it is possible to objectively see and compare the projects’ characteristics. Secondly, as art projects are the artists’ own creative work, backer involvement will not likely make the resulting art better or more desirable to the general audience, as there is no accounting for tastes. Technology-type projects are often successfully funded and backed compared to other crowdfunding categories (Crowddatacentre, 2015), and are therefore likely to have a sufficiently large pool of backers to research. On Kickstarter, the category technology has 3,529 successfully funded projects, with 1,819 of these projects securing funding of over $20,000, as per 5 November 2015 (Kickstarter 2015a).

Surowiecki (2004), namely ‘diversity of opinion’, ‘independence’ and ‘decentralisation’, were taken to arrive at a cut-off number of 500 backers or more. Additionally, Mollick (2014) shows that product deliveries on Kickstarter products is oftentimes delayed, while Gruner et al., (2014) notes that a period of 6 months after launch needs to be allowed to be able to measure new product success. Hence, the cut-off date for sample projects is a project end date between the start of the Kickstarter archives on July 22, 2012, and March 31, 2015, to allow sufficient time between project end date and time of measurement. The end date of the project was taken as a measure, as projects can vary in length between 1 – 60 days, with 30 days being most common (Mollick, 2014).

2.11 Conclusion

3. Methodology

The previous chapter elaborated upon the relevant literature concerning crowdfunding and customer involvement in the new product development process. It also developed hypotheses that test the possible relationships between the constructs introduced in the previous chapter. This chapter contains an explanation of the research paradigm on which this research is based, introduces the development of the primary research instrument, and addresses the ethical considerations that apply for this study.

3.2 Research paradigm

The choice for the particular research methods in this thesis was based on certain assumptions towards the world in general (ontology), and how to best research this (epistemology) (Tadajewski 2004). In this research, the theoretical framework is based on positivism, which belongs under the larger general umbrella of objectivism (Adams et al., 2007, Crotty, 1998)1_.

Objectivism as an epistemology and (post-)positivism as a theoretical perspective leads to the choice for a quantitative research paradigm, as discussed by Jonker and Pennink (2010). In accordance with this paradigm, the research is deductive in nature (Jonker and Pennink, 2010). This might be a surprising choice for research on a relatively new topic. However, as the relationships formulated in the hypotheses have been researched in other contexts before, empirical research is appropriate to test these relationships in the new setting of crowdfunding. Following the advised process for quantitative research taken from Jonker and Pennink (2010), this means that, initially, existing concepts and literature from peer reviewed journals are introduced and reviewed. Then, a conceptual model based on existing constructs is developed, whose relationships are then tested in a quantitative fashion. The data required to accept or reject the hypotheses are gathered through a survey, in which constructs are !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

1_{!This implies that for this research, the assumption is made that the world can be measured,}

and that these measurements yield facts rather than socially constructed items (Crotty, 1998, Creswell, 2014). Some theoretical frameworks, such as subjectivism and social

operationalised in multiple close-ended questions. Survey research is non-experimental, and especially suited to describe trends, correlations or opinions, as happens in this research (Creswell, 2014). The unit of analysis in this research will be each individual product that has been the subject of a crowdfunding campaign. For the sake of clarity, the research process presented in this section is made visible using the Research Pyramid introduced by Jonker and Pennink (2010):

! Figure 3.2

3.3 Primary data collection instrument

differences are expected to be non-existent (Malhotra and Peterson, 2001). All questions had seven-point Likert scales, which is ideal as it has an optimal fit between the nuance possible in respondents’ answers, decrease of use of the ‘neutral’ option, short test time, and clarity to the respondent (Matell and Jacoby, 1977). Responses were collected through the online survey programme Qualtrics, which has the advantage of being low-cost, non-intrusive and highly convenient for respondents (Malhotra and Peterson, 2001). The names of the projects and the fact that a Kickstarter campaign was ran for them were mentioned in the initial contact messages, so that respondents knew which product the survey dealt with. This was repeated in the intro message and statements above the questions (See appendix A). This resulted in the questionnaire presented on the next page.

3.4 Ethical considerations

4. Results

In this chapter, the results of the study are presented. First, data characteristics are discussed and a preliminary analysis conducted. Afterwards, the choice for multiple linear regression as a method of analysis is addressed and its assumptions explored. Then, the correlations between the different constructs are examined, after which they are researched further through conducting regressions, first with the main effects and then with the control variables. Finally, the hypotheses are tested and the results described.

4.2 Preliminary data analysis

uncommon phenomenon with a survey-design research (Hair et al., 2014). However, as nonresponse might bias the results, it is dealt with through excluding cases that miss 10% or more of their answers (Hair et al., 2014). For the remaining missing values, Little’s MCAR test was run in order to check randomness of missing values, returning no significance. In terms of variables, one of the consumer knowledge questions (‘we rarely/regularly search and collect information about our competitors) showed a nonresponse rate of 50%, and was therefore omitted from further analysis. Outliers are unlikely to occur in this design, as all answer categories are restricted from 1 – 7. This results in a cleaned, working dataset of (N=74), which is above Hair et al. ’s (2014) threshold value of 15-20 observations per dependent variable.

4.3 Further data analysis and hypothesis testing

Then, the psychometric properties of the survey items are assessed using SPSS 22.0, the results of which are found in Appendix B. The means range from 2,12 to 6,11, and the standard deviations from 0,78 to 2,14. Normality is checked through assessing skewness, or the symmetry of the items, and kurtosis, which assesses the shape of the distribution in terms of its steepness/flatness, as advised by Field (2009). In this set of variables, PI2, PI3 and PA3 show kurtosis values higher than Field’s (2009) advised threshold, indicating a leptokurtic distribution rather than a normal one. For the sake of normality, these values are thus eliminated. No abnormal skewness values were found. This in addition to the fact that the sampling distribution tends to be normal for samples larger than N=30, normality for the remaining data is assumed (Field, 2009). Reliability was measured using Cronbach’s alpha, which is above the threshold value of 0,7 for all operationalisations except R&D intensity (Field, 2009). For this construct, α is 0,456, but it jumps to 0,741 if item RD3 is deleted, which is done. No further adjustments to the data were made.

effects on the results. In the cleaned dataset, normality can be assumed as addressed in the previous paragraph. The normal distribution of residuals, another important assumption, is checked and assumed through plots of the regression of standardised residuals, as shown in Appendix C. Multicollinearity is not problematic in this sample as all VIF-values are close to 1, which is well below the cut-off score of 10 (Belsley et al., 2004). Additionally, the Durbin-Watson statistic to measure independent errors is close to 2 in all cases, indicating independence of errors (Field, 2009). In order to arrive at meaningful variables to analyse, reverse-coded questions were transformed and respondents’ answers on separate questionnaire items were summarised to their respective cumulative variable by taking the median. This is more appropriate than the mean as the intervals between values on a Likert scale may not be assumed of equal size (Cohen et al., 2000). Potential problems with multiple regression analysis as pointed out by Hair et al., (2014) are that smaller sample sizes such as the one in this research might not contain much statistical power, i.e. “the probability of correctly rejecting the null hypothesis when it should be rejected” (p. 9), and its results might not be very generalisable to the general population.

Table 4.1 Overview of Correlations

1 2 3 4 5 6 7 1. Backers as information source Pearson Correlation 1 Sig. (2-tailed) 2. Backer as

co-creator Pearson Correlation ,538

** ₁

Sig. (2-tailed) ,000 3. Product

Innovativeness Pearson Correlation -,005 -,229

* ₁ Sig. (2-tailed) ,969 ,048 4. Product Advantage Pearson Correlation ,118 ,070 ,437** ₁ Sig. (2-tailed) ,313 ,550 ,000 5. Absorptive Capacity Pearson Correlation ,196 ,187 ,072 ,429** 1 Sig. (2-tailed) ,112 ,131 ,562 ,000 6. R&D

Intensity Pearson Correlation ,148 ,182 -,096 ,163 ,403

** ₁

Sig. (2-tailed) ,243 ,150 ,448 ,197 ,001 7. Competitor

Knowledge Pearson Correlation ,272

* _{,127 ,184 ,180 ,223 ,204 1}

Sig. (2-tailed) ,031 ,319 ,149 ,157 ,081 ,108 **. Correlation is significant at the 0.01 level (2-tailed).

Above, correlations are presented in table 4.1 in order to explore the preliminary relationships between different variables. Six variables are significant at p ≤ 0,05, in a two-tailed test. The only negative significant correlation is between using the backer as co-creator and product innovativeness. Further interesting findings are positive correlations, two-tailed and significant at the p ≤ 0,05 level between product innovation and product advantage, product advantage and absorptive capacity, absorptive capacity and R&D intensity, backer as an information source and backer as co-creators, and backer as an information source and competitor knowledge. In order to examine the relationships between the variables in the hypotheses in more detail, two regressions are run per hypothesis. The first only contains the relevant dependent variable and independent variable. In the second, the influence of the moderating variables is tested following Baron and Kenny’s (1986) guidelines on incorporating moderating variables. They indicate that a moderating effect of a variable can be proven by if the interaction term (independent variable*moderating variable) is significant. These regressions were executed in SPSS using the guidelines of Laerd Statistics (2015). If a moderating effect exists, its size will be discussed separately.

Table 4.2 Relevant measures for interpreting multiple linear regressions

Name Measurement Outcome

ANOVA “Whether the model is significantly better at predicting the outcome than using the mean as a ‘best guess” (Field, 2009, p. 236)

If p ≤ 0,05, the observances in this model are unlikely to have

happened by chance R2 “How much variability in the outcome is

accounted for by the predictors” (Field, 2009, p, 235)

The closer R2 is to 1, the larger the amount of variance that is

explained by the predictors Beta/β “The number of standard deviations that the

outcome will change as a result of one standard deviation change in the predictor” (Field, 2009, 239)

“The ‘importance’ of a predictor in the model” (Field, 2009, 239) which is standardised and thus a more reliable predictor than b-value t-values “Whether the predictor is making a

significant contribution to the model” (Field, 2009, 239)

significant at (p = 0,001) and (p = 0,003), and significance of absorptive capacity on product advantage in the direct effect model (β = 0,424 for p = 0,001). A summary of the results following the example by Cui and Wu (2015) is presented in table 4.3.

Table 4.3 Summarised results of regressions

Independent variables Product innovativeness

(PI)

Product advantage (PA)

β t-value β t-value

Backer involvement

Backer as an information source (CI) -0,005 -0,039 0,118 1,017

Backer as co-creator (CC) -0,229 -2,014* 0,070 0,601

Control variables

4.4 Conclusion

In this chapter, the results from the data collection were introduced. The process of data cleaning and preparation is described, after which the choice for multiple linear regression is explained. Then, the assumptions for multiple linear regression are checked through SPSS output, that can be found in Appendices B, C, and D. After checking the assumptions, the correlations are presented in order to provide a preliminary overview of the relationships. This yielded quite surprising results, as it showed that backers as co-creators negatively impacted product innovativeness. This relationship was mediated by competitor knowledge. Main effects for the subsequent hypotheses were insignificant, though H2A and H2B showed a significant effect of absorptive capacity. An overview of the hypotheses and their results is given below.

Table 4.4 Results of hypothesis testing

No. Hypothesis Result

H1a The involvement of backers of a crowdfunding project as an information source (CI) has a positive effect on the innovativeness of the resulting product.

Rejected

H1b The involvement of backers of a crowdfunding project as co-developers (CC) has a positive effect on the innovativeness of the resulting product.

Rejected

H2a The involvement of backers of a crowdfunding project as an information source (CI) has a positive effect on product advantage.

Rejected

H2b The involvement of backers of a crowdfunding project as co-developers (CC) has a positive effect on product advantage.

5. Discussion

This study researches the influence of non-monetary backer involvement on crowdfunding projects. In line with previous theory and based on the relational view of the firm, hypotheses were developed that test the influence of backer involvement as information source or co-creator on product advantage and product innovativeness. This chapter connects the results from chapter 4 with the research objective and the research questions, and puts the results into context. Finally, the research’s limitations are discussed, and recommendations for future research outlined.

5.2. Discussion of the results

5,39, 6,08, and 5,93 out of 7 in the questions on innovativeness. These results are somewhat in congruence with the findings of Menguc et al., (2014), who find a negative interaction effect for customer involvement when the innovation is radical. However, they look at the product’s design only, and thus deal with another phase in the NPD process. A possible reason Menguc et al. (2014) give is that customers are more likely to provide input based on their current knowledge, and do not aim to solve their latent needs. In H1B, a significant interaction effect is also noted for competitor knowledge. If this interaction term is included, the β’s of both variables is larger negative than in the main effect. This is in contrast with the findings of Li and Cantalone (1998), who find a positive direct effect. However, they did not differentiate between radically innovative and incrementally innovative products, and thus the overall value they find can be positive while that of radically innovative products only might still be negative. The other hypotheses are not supported. However, in H2A and H2B, an interesting effect is measured when including absorptive capacity in the model. The interaction effect is not significant, but the direct effect of absorptive capacity on product advantage is, with a good model fit in both cases. This was expected, as an influence of absorptive capacity on competitive advantage, of which product advantage is a component, is shown by Cohen and Levinthal (1990) and Jansen et al., (2005).

wrongly. However, as the mean score on absorptive capacity, which measures this ability in the sample, was 5,34 out of 7, this chance seems small. With this evidence and the nonsignificance of the results, backers probably then provide other valuable information to entrepreneurs. In the literature, e.g. information on the potential market and its demand and validating feedback on the entrepreneur’s idea are mentioned (Scholz, 2015). Further research in this area is thus advised. Backers as co-creators did not have a significant impact on product advantage. Building on the same logic as above, co-creating backers are more rare than information-giving backers, with a mean of 3,7 out 7. Absorptive capacity remains equal, and so here, too, it is possible that backers that co-create improve the product in other ways than adding to the innovativeness or product advantage. A last absent correlation was the influence of R&D intensity on product advantage, which is very significant in Li and Cantalone’s research (1998). However, many entrepreneurs in the sample indicated that they do not have formal R&D processes and investments, possibly explaining the lack of a relationship.

5.3 Managerial implications

“You would think that Kickstarter is about projects but that's the tip of the iceberg. What makes Kickstarter special is what lies underneath. Backers. People.” Respondent #54.

This quote is from an e-mail received from a respondent in this research, outlining his thoughts on the subject. Multiple respondents indicated their interest in the matter of backer involvement, and thus, the findings of this research are relevant to them. As three hypotheses expressed no, and one a negative relationship, it is important for entrepreneurs to realise that product innovativeness and product advantage are likely not improved through backer influence. However, absorptive capacity has been identified as a significant predictor for product advantage. Knowing that the capability to learn and apply knowledge will positively impact the advantage of a product might help justify investments of time and money in this process. Additionally, the negative interaction effect for competitor knowledge indicates that final products will become less innovative when the competitor knowledge increases. Lastly, as anecdotal evidence shows that entrepreneurs value the relationships between themselves and their backers, it is important not to disregard backer influence as a result of the neutral or negative results of this study, as this might have positive influences on other aspects of the project.

5.4 Theoretical implications

method, thus attempting to bridge the gap between business practice and business as an academic discipline.

5.5 Limitations of research and suggestions for future research

This research is subject to multiple limitations, which are addressed in this section along with suggestions for future research. The generalisability of the results of this study is diminished by its methodology, particularly through conducting a cross-sectional study of only one crowdfunding platform with a relatively small sample size and a non-probabilistic sampling method. Additional cross-validating research on different crowdfunding platforms, with different types of products, and larger samples is thus advised, as causal inferences are hard to draw from one cross-sectional study. Furthermore, results can be compromised through the measurement of the constructs, as self-report bias might exist in survey items asking entrepreneurs about their own product’s performance, while common methods bias is possible in behavioural studies (Podsakoff et al., 2003). Additional research is necessary into crowdfunding to be able to assess and counteract these limitations. This study is to some degree exploratory, and thus a first step in the body of research on backer involvement in crowdfunding. Therefore, more research on crowdfunding as a phenomenon is necessary. This study is limited as it addresses only backer influence on rewards-based crowdfunding, while this influence might also occur in e.g. equity-based crowdfunding, where backers collectively own equity and thus have long-term formal voting power (Wroldsen, 2013, Mollick, 2014). Additional insight can be gained through looking at the success of crowdfunded projects in the longer term, especially in terms of financial results. As anecdotal evidence from entrepreneurs suggests an important role of backers, despite the evidence in this study, more research into the other roles of backers is advised.

5.6 Conclusion

instrument developed. However, after testing the data obtained from a non-probabilistic sample of 74 Kickstarter entrepreneurs, none of the hypotheses were confirmed, with one yielding a significant negative effect. The reasons for this non-significance are discussed in chapter 5, and can be both theoretical and statistical. The research is subject to multiple limitations, both methodologically and theoretically, but nonetheless closes the gaps in the literature concerning what happens to a project after its crowdfunding campaign has ended, and has shed light for both academics and practitioners on one aspect of the complex relationship between backers and entrepreneurs.

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