The effect of crowdsourcing on the purchase intention of the consumers

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The effect of crowdsourcing on the

purchase intention of the consumers

Master thesis, final version Name: Babs Niele

Student number: 10868917 First reader: Carsten Gelhard

MSc Business Administration, Strategy track Date: 30th of August 2015

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1 Disclaimer

“This document is written by Student Babs Niele who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document are 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 contents.”

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Abstract

The aim of this study is to present a critical synthesis of empirical evidence about the factors that influence the purchase intention of consumers when involved in crowdsourcing. More firms acknowledge that using the knowledge of consumers and co-creating new products or services is essential. Crowdsourcing is one of the value co-creation methods to gather this knowledge. It is indicated that crowdsourcing is not only used as a marketing tool or an easy way to get to know the wishes and demands of consumers, but also as a strategic tool to increase the product turnover. However, although many studies have examined why people engage in crowdsourcing, it has not been examined if the people who engage are eventually willing to purchase the item as well. Therefore the effect of participation involvement on the purchase intention, together with additional factors of influence is examined in this thesis. Data was collected through a self-administered survey from 82 respondents who participated in a crowdsourcing project. This study could not provide proof that the participation

involvement has a direct effect on the purchase intention of the consumers. However, this study provided proof that being consumer orientated, being innovative as a firm, and the fact that consumers can gain benefits from participating, play a significant role in the purchase intention of the consumer.

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Table of contents

Abstract ... 2 1. Introduction ... 4 2. Literature review ... 8 2.1 Crowdsourcing ... 8 2.2 Purchase intention ... 11

2.3 Perceived innovation ability ... 13

2.4 Consumer orientation ... 15

2.5 Consumer benefits ... 17

2.6 Expertise of the consumers ... 19

2.7 Brand equity ... 21

3. Methodology ... 24

3.1 Sample ... 24

3.2 Measurement of variables ... 25

3.2.1 Independent and dependent variable ... 25

3.2.2 Mediating variables ... 26 3.2.3 Moderating variables ... 27 3.2.4 Control variables ... 27 3.3 Research design ... 28 4. Results ... 30 4.1 Correlation analysis ... 30 4.2 Direct effects ... 33 4.3 Mediation effects ... 34 4.4 Moderation effects ... 38

5. Discussion of research findings ... 44

5.1 Theoretical and practical implications ... 44

5.2 Limitations ... 48

5.3 Further research ... 49

6. References ... 51

Appendix ... 57

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1. Introduction

Crowdsourcing is an innovation method that has emerged in the business world less than 10 years ago and has become an interesting topic to investigate (Brabham, 2008). Crowdsourcing is a popular production model that makes use of the ability to capture ideas from the crowd via online channels to develop new products (Brabham, 2008). Several companies are involved in crowdsourcing with success, such as Heineken, Lego, Dell, InnoCentive, Threadless and Netflix (Afuah & Tucci, 2012; Brabham, 2008; Majchrzak & Malhotra, 2013). Some companies, such as Lego and Lays, use Facebook as source to gain knowledge from consumers by organizing a contest and incentivize consumers if their ideas win (Bunskoek, 2014). The trend in the rising amount of companies who are making use of crowdsourcing to produce new consumer products makes it a valuable and interesting topic to further investigate.

Crowdsourcing is one of the latest developments in the field of open innovation (Enkel, Gassmann, & Chesbrough, 2009). For this reason it is logical that crowdsourcing is related to, and sometimes confused with, the concept open innovation. Crowdsourcing and open innovation are both falling within the same paradigm, however crowdsourcing differs from open innovation on two points (Schenk & Guittard, 2011). Firstly, crowdsourcing has a different focus. Open innovation particularly focuses on innovation processes, while

crowdsourcing focuses on tasks which are information or knowledge related involving low fixed equipment costs (Schenk & Guittard, 2011). Secondly, open innovation mainly focuses on knowledge flows between firms, while crowdsourcing focuses on knowledge flows between the firm and the crowd (the consumers) as a large set of anonymous individuals (Schenk & Guittard, 2011).

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5 The models around crowdsourcing are still under development and it is expected that there are still a few trends within crowdsourcing to come (Gegenhuber, 2014). Several

researchers indicate that crowdsourcing is a promising method to gather new ideas, compared to gathering new ideas internally or to outsource it to an exclusive contractor (Afuah & Tucci, 2012; Majchrzak & Malhotra, 2013; Poetz & Schreier, 2012). Most studies about

crowdsourcing focus on how to empower consumers to participate in a crowdsourcing practice, and if the ideas of the consumers can compete with the ideas that the professionals generate (Afuah & Tucci, 2012; Ågerfalk & Fitzgerald, 2008; Füller, Mühlbacher, Matzler, & Jawecki, 2009; Majchrzak & Malhotra, 2013; Poetz & Schreier, 2012; Schreier, Fuchs, & Dahl, 2012). However, in the study of Kleemann, Voß, & Rieder (2008), it is indicated that companies are making use of crowdsourcing not only with the purpose to create new products, but also to reduce costs, to become more efficient and to increase the product turnover. If a company wants to increase the turnover of produced products through a crowdsourcing project, it is interesting to know if consumers who participate in a

crowdsourcing project actually are willing to purchase the product. If there is a significant effect between the participation involvement in a crowdsourcing project and the willingness to purchase, crowdsourcing could also be used as a strategic tool to attract more and new consumers and increase the product turnover. Understanding the determinants of consumers’ purchase intention of the value co-created product or service could provide valuable

suggestions. It could give insights on which aspects a company should focus when using crowdsourcing as a strategic tool. For this reason, this study measures if the participation involvement in a crowdsourcing project has an influence on the purchase intention. This leads to the followingquestion:

‘What is the influence of the consumer participation involvement on the consumers’ purchase intention of the co-created product through crowdsourcing?’

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6 This research question can be substantiated by various theories. A well-known theory that suits this study is the Resource Based View theory (RBV). Crowdsourcing is a way to enable the consumer to collaborate with the company, these interactions are the key to unlock new information and new sources of competitive advantage (Prahalad & Ramaswamy, 2004). This competitive advantage can be explained by the RBV. Through the interactions that take place within crowdsourcing the company gets valuable knowledge of the needs of consumers and get access to innovative ideas. This way a new resource can be created which satisfies the four attributes: valuable, rare, imperfectly imitable and non-substitutable (VRIN) (Barney, 1991) and a competitive advantage is gained.

Another theory that relates to this study is the relational marketing theory, since crowdsourcing is about a relationship between the consumer and the company. This relationship should be managed, which is explained by the relational marketing theory. Grönroos (1997) describes that firms can choose between following a relational strategy or a transactional strategy. It depends on the profitability and suitability which strategy should be chosen. It is stated that value creation goes beyond the product, which indicates that a relational strategy will definitely make sense (Grönroos, 1997). The value perception of the consumer can be influenced by how involved the consumers are in the final development or design of a solution. The value creation in a relational context can be managed by a firm to focus on the resources it owns and by developing competencies to acquire and manage these resources (Grönroos, 1997). By using crowdsourcing, firms can better anticipate on the demand of the consumers and can get valuable knowledge of how to maintain the relationship between the firm and the consumer. Since the consumer and the firm collaborate together in a merged, coordinated, dialogical and interactive process, both value is created for the firm as for the consumer, they co-create value (Grönroos, 2012).

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7 In the next chapter a critical synthesis is given about the relevant constructs for this study and the hypothesis are described. Subsequently, chapter three outlines the methodology. The data collection and research methodology are discussed in this third chapter. The results are discussed in chapter four. Finally, the fifth chapter presents the discussion, limitations and suggestions for further research.

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2. Literature review

The theories and concepts around crowdsourcing will still develop in the following years and it is expected that there are still a few trends within crowdsourcing to come

(Gegenhuber, 2014). This study aims to contribute to current literature by aiming to measure the factors that influence the purchase intention of consumers when involved in

crowdsourcing.

This literature review reflects on the aspects that are relevant in order to display the relationship between the participation involvement in crowdsourcing and the purchase

intention of the consumers. First, the main subject, crowdsourcing and purchase intention will be discussed. This is followed by a discussion of the factors that drive the purchase intention. Subsequently, the moderating variables consumer competences and brand equity are

discussed.

2.1 Crowdsourcing

According to Prahalad & Ramaswamy (2000) firms must learn from, and collaborate with the consumers to create values that meet the individual and the dynamic needs.

Nowadays, consumers play an important role in creating and competing for value (Prahalad & Ramaswamy, 2000). One of the first researchers who wrote about the involvement of

consumers is von Hippel (2005). He states that user-centered innovation processes have an advantage over manufacturer-centric innovation processes (Hippel, 2005). The former process is different from the latter process, since in the manufacturer-centric innovation process the role of the users is only to have a need, where in the user-centered innovation process the users have the task to design and produce the new product (Hippel, 2005). It is clear that the competences of the consumers become an important source to gain a competitive advantage.

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9 Through crowdsourcing, a company can get valuable knowledge of the needs of

consumers. In addition, they can get access to innovative ideas which the competitors do not have access too, if they are the first ones to gather this knowledge. According to the RBV VRIN resources are created and a competitive advantage can be gained. However, it is difficult for a company to gain a sustained competitive advantage, since the ideas are collected through social media or platforms which are open for everybody. Competitors can thus, gain access to this knowledge too. It is therefore important that the knowledge and ideas from the consumers are combined with the knowledge of the company to gain a sustained competitive advantage (Kogut & Zander, 1992). This makes it harder for competitors to imitate them, since they are unaware of where the competitive advantage comes from (Barney, 1991).

Crowdsourcing is made possible because of the development of web 2.0 (Kleemann et al., 2008). “Web 2.0 refers to the social use of the Web which allows people to collaborate, to get actively involved in creating content, to generate knowledge and to share information online” (Grosseck, 2009). Different online channels are used for crowdsourcing; social, web pages such as Wikipedia or (mobile) platforms (Yan, Marzilli, Holmes, Ganesan, & Corner, 2009). Consumers play a big role in the whole crowdsourcing process. With this role, a new type of consumer is emerged; “the working consumer” (Kleemann et al., 2008, p. 2).

Consumers become co-workers of the company, which makes it important for the company to motivate, influence and encourage the consumers. The value that is created through that collaboration is created for both the consumer and the company. The value perception of the consumer depends on how involved the consumers are in the final development or design of a solution. This can be influenced by the company. The value creation in a relational context can be managed by a company to focus on the resources it owns and by developing

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10 crowdsourcing as a strategy of the company it is possible to create new value for both the company and the consumers. They co-create value (Grönroos, 2012). Since value is created and perceived by the consumer it is plausible to assume that this will have an influence on the purchase intention. By using crowdsourcing it is possible for the firm to appropriate more value to themselves. This is due to the fact that the firm is able to get free knowledge from the consumer and does not have to involve a specialist, who otherwise wants to receive a share of the value created (Brandenburger & Stuart, 1996). Since the consumers are more involved, logically they want to receive a larger share of the value created. However, consumers do not always have to be incentivized with money. It is proven that people who participated in a crowdsourcing project, not only participated for the money that can be earned, but also because of other benefits such as enhancing product knowledge, reputation and enjoyment (Nambisan & Baron, 2009).

Crowdsourcing can be seen as a user-centered innovation process through the internet, with the goal to reach ‘crowds’ of people, who can help to solve problem or invent new products which are time consuming and costly tasks (Yan et al., 2009). Besides the fact that crowdsourcing is used to reduce the product development time, companies can have other motives such as; “cost reduction, productivity gains, increase of turnover and quality improvement using consumer knowledge” (Kleemann et al., 2008, p. 20). However, except advantages, crowdsourcing has disadvantages as well. When using crowdsourcing, profits are not guaranteed and investments in, inter alia, marketing has to be done which makes the company more vulnerable. In addition, responsibilities to develop a new product or service are transferred to the consumer, while not knowing if they have sufficient expertise

(Kleemann et al., 2008). Brabham (2008) argues that there are also costs for the consumers. He states that if the high quality labor of the consumers in comparison to what the received value is too low, it will resemble in a slave economy (Brabham, 2008). Besides,

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11 crowdsourcing can also replace certain jobs, which can eventually result in firing employees (Brabham, 2008).

Although some companies, such as Threadless, iStockphoto, InnoCentive have proven that crowdsourcing can be successful (Brabham, 2008), crowdsourcing does not always have to be successful. The study of Afuah & Tucci (2012) highlights the fact that the

successfulness of crowdsourcing depends on the type of problem. According to Afuah & Tucci (2012) there are five factors which should be considered when crowdsourcing the problem; “(1) the characteristics of the problem, (2) the extent to which the focal agents needs to perform distant search to solve the problem internally or find a designated contractor, (3) the extent to which the crowd has potential solvers that are likely to self-select to solve the problem, (4) how the solutions that are generated can be evaluated effectively and efficiently and (5) the pervasiveness of low-cost information technology that facilitates the process of crowdsourcing” (Afuah & Tucci, 2012). This is shown in the study of Chanal & Caron-Fasan (2010). It is observed that the firm has difficulties reaching a large community who are willing to collaborate. This observation is in line with other results found by Dahlander & Magnusson (2008). Lichtenthaler & Ernst (2008) acknowledge that these new marketplaces have not met the great expectations of most researchers and practitioners. However, they refer to these marketplaces, which become available through the internet, as a promising avenue since they go beyond providing infrastructure and include additional consulting (Lichtenthaler & Ernst, 2008).

2.2 Purchase intention

Purchase intention corresponds to the desire of consumers to purchase a product or service from a company (Liao & Hsieh, 2012). As mentioned in chapter 2.1, it is plausible that the purchase intention will be influenced when value is created through cooperation of the company and the consumers. This could be explained by the fact that the consumers will

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12 perceive more value. The perceived value by the consumers includes the core product and/or service and the additional services that are offered (Grönroos, 1997). In addition the prices and costs that occur from participating in a value co-creation practice are as well taken into consideration by the consumers (Grönroos, 1997). The purchasing behavior will be favorably influenced if the benefits outweigh the costs and if consumers perceived the co-creation practice as positive (Grönroos, 1997).

Several studies have focused on the purchase intention of consumers when involved in a value co-creation practice. Kamali & Loker (2002) conducted an experimental study to examine if the purchase intention would increase if consumers where involved in

development process. This study showed that an increased level of interactivity was a

motivation to purchase the items (Kamali & Loker, 2002). Another study investigated if there is a difference between the purchase intention for a product or service when it is designed by professional designers or by common users (Schreier et al., 2012). This particular study showed that the purchase intention of consumers is substantially higher for products which are designed by users instead of professional designers (Schreier et al., 2012). Also in the study of Fuchs & Schreier (2011) the focus was on this difference. However, they made a distinction between two different kinds of consumer empowerment. On the one hand were consumers that were able to select the product that needed to be produced. On the other hand were consumers that are the ones who created the new products (Fuchs & Schreier, 2011). This study showed that consumer empowerment leads to better corporate attitudes and behavioral intentions in comparison to the sketched situation in which a company does not embrace consumer empowerment (Fuchs & Schreier, 2011). For both situations this was applicable.

In these studies purchase intention is mostly investigated through an experimental study. To make the findings more generalizable it is interesting to do a non-experimental survey design. This way it can be stated if consumer empowerment in product development

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13 really has an influence on the purchase intention. On the basis of previous research it is likely that people who participate in a crowdsourcing project are as well willing to purchase the product or service.

H1: Consumer participation in crowdsourcing will have a positive effect on the consumers’ purchase intention of the crowdsourced product/service.

2.3 Perceived innovation ability

For innovations to be successful it is essential to have a consumer-centric perspective, (Kunz, Schmitt, & Meyer (2011). A company that makes use of crowdsourcing should keep in mind that consumers not only judge the new product, but also observe a range of the company activities to judge the firm’s overall innovativeness (Kunz et al., 2011). A firm’s innovation ability is not only about the outcome of the firm’s activity, but is also an enduring process in which a firm is open to new ideas and is working on new solutions (Kunz et al., 2011). To successfully value co-create with the consumers, the company should be prepared to receive the consumers’ input and make use of it (Grönroos, 2012). As highlighted by the relational marketing theory, the company should offer the right resources for the consumers to collaborate successfully (Grönroos, 2012). These resources, such as new technologies, knowledge of the companies employees, ways of managing the consumers’ time should be up-to-date and encourage cooperation (Grönroos, 1997). This will stimulate the interaction between consumers and between the consumer and the company as well.

Several studies have examined the effect of a companies’ innovation ability and which factors have an influence on the companies’ innovation ability. In the study of Calantone, Cavusgil, & Zhao (2002) is found that the development of new knowledge is crucial for the firm’s innovation ability and the firm’s performance. Organizational learning is an important process in this. This study showed that firms who are committed to learning

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14 attempt to get a full understanding of the environment, including consumers, competitors and emerging technologies (Calantone et al., 2002). According to the RBV this is as well

important to create eventually a sustainable competitive advantage, since you want to stay ahead of the competitors (Barney, 1991; Kogut & Zander, 1992). The study of Calantone, Chan, & Cui (2006) showed that firms innovativeness is positively related to the firms performance. Firms performance was measured through the return on investments, return on assets, return on sales and overall profitability (Calantone et al., 2006). This has been proven as well by Kunz et al. (2011). This study provide proof that the perceived innovativeness of the firm has an effect on the consumers behavior and eventually on the firm’s success (Kunz et al., 2011).

The experimental study of Schreier et al. (2012) not only provided proof that the purchase intention of consumers is substantially higher for products designed by users instead of professionals, but also focused on the mediating effect of perceived innovation ability. This study provided proof that firms who pursue common design by users will be perceived as more innovative than firms who pursue a design by a professional. Likewise, it is proven that perceived innovation ability has a positive mediating effect on the relationship between common design by users and purchase intention and a negative mediating effect on the relationship between design by professional and purchase intention.

When accessing previous studies it is showed that a consumer-centric perspective is important for innovations to be successful. It is important that the consumers are involved in the development process to understand the consumer needs. It is proven that participation involvement has an influence on how the innovation ability of the firm is perceived by the consumers. Subsequently, that the perceived innovation ability has a positive influence on the firm’s performance and the purchase intention of consumers. However, most studies only focus on one of two relationships. The study, of Schreier et al. (2012), that focused on both

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15 was an experimental study where the focus lied on common design by users versus design by professional. The mediating effect of perceived innovation ability has not been tested with consumers who actually participated. Thus, on the basis of previous studies the following hypothesis is suggested.

H2: Perceived innovation ability of the firms mediates the relationship between consumer participation in crowdsourcing and the consumers’ purchase intention, so that consumer participation in crowdsourcing leads to an increase in perceived innovation ability (2a), which in turn positively influences the consumers’ purchase intention (2b).

2.4 Consumer orientation

Consumer orientation refers to the ability of the firm to anticipate and respond to the need of the consumer (Brady & Cronin, 2001; Deshpandé, Farley, & Webster, 1993; Fuchs & Schreier, 2011). According to the relational marketing theory it is important to identify, establish, maintain, enhance and when necessary terminate relationships with consumers so that the objectives of all parties are met (Grönroos, 1997). Since crowdsourcing is a strategy where consumers play a significant part in the development process it is important for the company to focus on the consumers. Several studies suggest that firms who are consumer orientated are more successful. For these firms it is easier to identify the consumers’ needs, which makes it easier to deliver the right product and services (Deshpandé et al., 1993; Fuchs & Schreier, 2011; Kelley, 1992; Stock & Hoyer, 2005). The study of Lengnick-Hall (1996) highlights the fact that the competitive quality of a firm is not only based on specific systems, continuous improvement, high productivity and teamwork, but also on the consumer

orientation of the firm. This article states that to achieve this consumer orientation, it is important to not only actively collect information from the consumers, but also to design systems to empower the consumers to participate in the whole process (Lengnick-Hall, 1996). A study that has investigated this relationship is the study of Fuchs & Schreier (2011). This

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16 study focused on the relationship between consumer empowerment and consumer orientation. The results of this study show that consumer empowerment has a direct positive effect on the perceived consumer orientation (Fuchs & Schreier, 2011), which is in line with the

assumptions made by Lengnick-Hall (1996).

Some other studies specifically focused on the relationship between consumer orientation and the effect on the business performance of the firm and consumer behavior (Brady & Cronin, 2001; Deshpandé et al., 1993). The study of Deshpandé et al. (1993)

highlighted this relationship and focused on the effect of consumer orientation on the business performance. This study was performed at a Japanese firm and showed that being consumer orientated is one of the key determinants of business performance. A study, which showed results in line with this study is the study of Brady & Cronin (2001). They specifically investigated if being a consumer oriented firm has an effect on the service performance perceptions and the outcome behaviors of the consumers. They proved that being a consumer oriented firm enhanced the perceptions of the quality of the firm, which has an influence on the consumers’ loyalty, purchase intention and positive recommendation (Brady & Cronin, 2001).

Previous research has indicated that consumer empowerment has an effect on perceived consumer orientation and that consumer orientation has an effect on the business performance and consumer behavior. However, consumer orientation has never been investigated as a mediating effect between participation involvement and willingness to purchase. Therefore, the following hypothesis is suggested.

H3: Perceived consumer orientation mediates the relationship between consumer participation in crowdsourcing and the consumers’ purchase intention, so that consumer

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17 participation in crowdsourcing leads to an increase in perceived consumer orientation (3a), which in turn positively influences the consumers’ purchase intention (3b).

2.5 Consumer benefits

A value co-creation practice, such as crowdsourcing, should already emphasize certain benefits a consumer can gain from participating to be successful (Deborah Roberts, Mathew Hughes, & Kia Kertbo, 2014). This is, highlighted by the relational marketing theory, due to the fact that consumers assess the quality of the product by what they get as an outcome of the whole participation in the value co-creation practice and how they have experienced the interactive part of the process (Grönroos, 2012).

To measure consumer benefits the “uses and gratification” framework is often used. This framework is mostly used in studies where the focus lies on the interaction between companies and consumers through the media or internet (Nambisan & Baron, 2009). In the article of Nambisan & Baron (2009) they have investigated why consumers voluntarily participate in online forums or virtual customer environments (VCE). Nambisan & Baron (2009) used the U&G framework to examine motivations. The U&G framework identifies four types of benefits that can be derived from participating in a value co-creation project through media. “(1) cognitive benefits that relate to information acquisition and strengthening of the understanding of the environment; (2) social integrative benefits that relate to

strengthening consumer’s ties with relevant others; (3) personal integrative benefits that relate to strengthening credibility, status, and confidence of the individual; and (4) hedonic or affective benefits such as those that strengthen aesthetic or pleasurable experiences”

(Nambisan & Baron, 2009). This study showed that several benefits, that where expected to increase when participating, are significantly related to actual participation in the VCE. Consumers do not only participate in these forums purely on altruistic or citizenship motives, but also expect to gain other benefits, such as enhancing product knowledge, enhancing

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18 reputation and enjoyment (Nambisan & Baron, 2009). Prahalad & Ramaswamy (2003)

highlight that these four types of benefits will in turn be influenced by the actual participation involvement. This is logical since consumers provide and share information, make

suggestions, and become involved during the value co-creation process. This is as well in line with the study of Deborah Roberts et al. (2014). In this study is highlighted that consumers must expect a benefit prior to collaborating with a firm in a value co-creation practice and that the consumers must believe that the benefits will be achieved (Deborah Roberts et al., 2014). The study provided proof that people who participated in a value co-creation practice actually achieved the benefits. It is stated that these people perceived the experience as enjoyable, positively stimulating and they refined their creative skills (Deborah Roberts et al., 2014).

Other studies focused on the effect of perceived consumer benefits on the purchase intention. The study of Chiu, Wang, Fang, & Huang (2014) showed that the perceived

benefits have a positive influence on the purchase intention and acknowledged the importance of the benefits consumers should receive when examining their purchase decision. In the study of Bridges & Florsheim (2008) this positive influence is proved as well. It is stated that when people have feelings of control and enjoyment while using the internet, this will have a positive influence on the purchase intentions. The study showed that when there is an

effective interaction and sufficient control people are more likely to purchase the item (Bridges & Florsheim, 2008).

Since it is proven that participation involvement will have a positive influence on consumer benefits, and consumer benefits can have a positive influence on the purchase intention, it is hypothesized that these situations can also be the case in a crowdsourcing environment.

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19 H4: Perceived consumer benefits mediate the relationship between consumer

participation in crowdsourcing and the consumers’ purchase intention, so that consumer participation in crowdsourcing leads to an increase in perceived consumer benefits (4a), which in turn positively influences the consumers’ purchase intention (4b).

2.6 Expertise of the consumers

Since crowdsourcing is a user-centered innovation process, the competences of the consumers become an important source to gain a competitive advantage, as already mentioned in 2.1. The eventual product produced via crowdsourcing depends on the knowledge, skills and insights of these consumers (Grönroos, 2012). For this reason it is important that the consumers possess the right skills, since consumers who are better skilled will be more co-creative, than consumers who are less skilled (Grönroos, 2012).

In the study of Füller et al. (2009) is described which competences a consumer should possess for their participation in the value co-creation project to be successful. It is stated that consumers should possess domain-specific knowledge and creativity-relevant processing skills. The study showed that people who have more expertise tend to perceive their participation as more active (Füller et al., 2009). Several other studies specifically

investigated the role of the competences and expertise of the consumers. Kunz et al. (2011) showed that the perceived innovation ability of the firm is based on the consumers’

information, knowledge and expertise. Thus, it is logical that perceived innovation ability of the firm will be higher when the consumer possesses more knowledge and expertise about the product or service. The study of Deborah Roberts et al. (2014) showed that individuals who participate in a value co-creation practice who possess the right competences and expertise, have an even higher potential to develop even better skills and competencies when

participating in a value co-creation practice. This is beneficial for the consumers who participate. Thus, it can be said that the effect between participation involvement and

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20 perceived consumer benefits will be stronger when the consumers possess the right

competences and expertise.

Although the role of the competences of the consumer is highlighted by some studies. No study specifically focused on if the expertise of the consumers will have an effect on the perceived consumer orientation. However, Brady & Cronin (2001) highlight in their study that the effect of consumer competences on consumer orientation should be further

investigated. They indicate that consumer competences probably will have an influence on how the consumer orientation is perceived.

On basis of these findings it is suggested that consumer competences will moderate the relationship between participation involvement and perceived innovation ability, consumer benefit and consumer orientation.

H5a: Consumer competences will moderate the relationship between participation involvement and perceived innovation ability, so that consumer with high competence level of innovation ability will perceive higher innovation ability than consumers with a lower competence level of innovation ability.

H5b: Consumer competences will moderate the relationship between participation involvement and perceived consumer orientation, so that consumer with high competence level of innovation ability will perceive higher consumer orientation than consumers with a lower

competence level of innovation ability.

H5c: Consumer competences will moderate the relationship between participation involvement and perceived consumer benefits, so that consumer with high competence level of innovation ability will perceive higher consumer benefits than consumers with a lower competence level of innovation ability.

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21 2.7 Brand equity

According to Heilbrunn (1995) the brand acts as an intermediary between the company and the consumer. It is a triadic relationship which is comparable to the triad between company, employee and consumer (Grönroos, 1995). In both relationships it is the responsibility of the company to keep the guaranteed promises. The model of Heilbrunn suggest that the brand provides a projection of meaning to the consumer (Heilbrunn, 1995). In addition there is an emotional link between the consumer and the brand which goes further than only the rational and economical aspects (Heilbrunn, 1995).

Thus, there is an important relationship between the brand, the consumer and the firm. However, brand equity is not evaluated in most of the studies about new product development and value co-creation practices. This is remarkable since consumers are influenced by the brand of the company (Heilbrunn, 1995). Despite the fact that the brand act as a intermediary between the company and the consumer, it is proven that brand equity is a driving force for a better firm performance (Lassar, Mittal, & Sharma, 1995). These are reasons why brand equity should be taken into consideration when conducting a study regarding crowdsourcing,.

Within crowdsourcing consumer-based brand equity plays a significant role, since the consumers are highly involved with the company. Consumer-based brand equity involves the reaction of the consumer to an element of the marketing mix (Keller, 1993). A great brand equity can provide many benefits for a firm, such as greater consumer loyalty, better

competitive position, larger margins and more favorable consumer response, including more willingness to purchase (Keller, 2001). Although the effect of brand equity has not been tested specifically within a crowdsourcing environment, the impact of brand equity on the firm performance has been tested thoroughly.

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22 Brand equity can be divided into several constructs. The most common used are brand loyalty, perceived quality, brand awareness, brand image and brand associations (Belén del Río, Vázquez, & Iglesias, 2001; Hong-bumm Kim, Woo Gon Kim, & Jeong A. An, 2003; Lassar et al., 1995). The study of Hong-bumm Kim et al. (2003) tested the direct relationship between brand equity and firm performance. They specifically focused on brand loyalty, perceived quality, brand image and awareness. These constructs showed that they have a positive influence on the financial performance. Another study that focused on the effect of brand equity is the study of Cobb-Walgren et al. (1995). They showed that the brand with the higher equity had a significantly greater preference of consumers and that their purchase intentions were higher. Yoo & Donthu (2001) proved as well that a better brand equity has a more positive influence on the purchase intention. Belén del Río, Vázquez & Iglesias (2001) focused on the moderating role of brand equity. Their study showed that the association of the brand with a function perceived as good, has a more positive influence on the purchase

intention. They examined brand associations of the consumer on four brand functions:

guarantee, personal identification, social identification and status (Belén del Río et al., 2001). So several studies have showed that having a brand equity that is perceived as good by the consumer will have more positive influence on the purchase intention. However, it has never been tested if brand equity is important for crowdsourcing as well. By testing the moderating effect of brand equity in this study, it could provide proof if the importance of the brand does apply for a firm which uses crowdsourcing. Based on previous findings the

following hypothesis is suggested.

H6a: Brand equity will moderate the relationship between perceived innovation ability and purchase intention so that consumer with a positive feeling towards the brand will be more willing to purchase the product.

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H6b: Brand equity will moderate the relationship between perceived consumer orientation and purchase intention so that consumer with a positive feeling towards the brand will be more willing to purchase the product.

H6c: Brand equity will moderate the relationship between perceived consumer benefits and purchase intention so that consumer with a positive feeling towards the brand will be more willing to purchase the product.

The suggested hypotheses lead to the following conceptual model:

Participation Involvement Willingness to Purchase

Perceived Innovation Ability of the Firm Perceived Consumer

Orientation Perceived Consumer

Benefits Consumer

Competences Brand Equity

H1 H4a H5c H2b H3b H4b H2a H3a H5b H5a H6c H6a H6b

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24

3. Methodology

This chapter describes the method of the study. Firstly, a description of the sample is outlined. Thereafter it provides an overview of the variables and items that are used in order to develop the questionnaire. In addition the corresponding reliabilities are discussed. Lastly, the

statistical procedure is explained. See appendix 1 for the complete questionnaire.

3.1 Sample

The sample of this study consists of people who have participated in a crowdsourcing project through social media. The respondents have been approached through social media, since more companies start making use of social media to involve their consumers into their value co-creation process. From the 146 people who started filling out the questionnaire, 99 completed the full questionnaire. Only the cases where no data was missing were analyzed and the ones that were not applicable were removed. After cleaning the data 82 cases remained (response rate 56%).

From these 82 respondents (Mage = 25.41, SDage = 6.76, age-range: 21 – 62 years) 52.4% were female. The majority of the respondents had a Dutch nationality (90.2%). Other nationalities were Belgian (2.4%), Greek (1.2%), Swiss (1.2%), Bulgarian (1.2%), Russian (1.2%), Chinese (1.2%) and Australian (1.2%). A small percentage of the sample had completed a secondary educational program (6.1%). Each of them had completed the pre-university education (VWO). 30.5% completed an educational program at an pre-university of applied sciences. One respondent (1.2%) had completed another type of education, namely international baccalaureate. The remaining and majority of the respondents (62.1%) had completed an educational program at the research university (34.1% bachelor’s degree, 28.0% master’s degree).

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25 3.2 Measurement of variables

To secure the validity of the constructs, all constructs were adopted from previous English studies in which the factor analysis had provided strong evidence of discriminant validity. In addition the reliability of the constructs was examined and checked if the

Cronbach’s α were above 0.70 (van Dalen & de Leede, 2009). In all studies the constructs had a Cronbach’s α greater than 0.70. For this study some of the items were slightly modified in a way that they fit better within this study. Most items were measured on a seven-point Likert scale. A few items were measured on a 10-point Likert scale. In addition, multiple items were used to measure one construct; this was done by a matrix type of question.

3.2.1 Independent and dependent variable

To measure the independent variable participation involvement the scale of Chan, Yim, & Lam (2010) was used. Participation involvement can be seen as ‘behavioral construct that measures the extent to which consumers provide and share information, make suggestions and become involved during the crowdsourcing process’ (Chan et al., 2010). The respondents were asked to what extent they disagreed or agreed with 5 statements. These statements were measured on a 7-point Likert scale from “1 = strongly disagree” to “7 = strongly agree”. One item was reversed coded.

The dependent variable, purchase intention, was measured by using the scale of

Schreier et al. (2012). Purchase intention corresponds to the desire of consumers to purchase a product or service from a company (Liao & Hsieh, 2012). Four items were measured on a 7-point Likert scale. Two of these items were measured on a scale from “1 = strongly disagree” to “7 = strongly agree”. The other two items were measured on a scale from “1 = very

unlikely” to “7 = very likely” and on a scale from “1 = very improbably” to “7 = very

improbably”. One of these items was reversed coded. The last item what would be the future purchase probability of products or services from this company was measured on scale from

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26 “0 = no chance, would never buy” to “10 = certain, would definitely buy). This last item was converted to a 7-point Likert scale before the results were analyzed.

3.2.2 Mediating variables

Perceived consumer orientation, consumer benefit and innovation ability were all expected to mediate the relationship between participation involvement and willingness to purchase. Perceived consumer orientation refers to the firm’s ability to satisfy the need of the consumer (Fuchs & Schreier, 2011). To measure this construct, items were adapted from Fuchs & Schreier (2011). The six items were measured on a scale from “1 = strongly disagree” to “7 = strongly agree”. Two of the items were reversed coded.

Perceived consumer benefits refer to the benefits that can be obtained from

participating in a crowdsourcing practice (Nambisan & Baron, 2009). Four kind of benefits can be distinguished: learning, social integrative, personal integrative and hedonic

(Nambisan & Baron, 2009). The items were adapted from the study of Nambisan & Baron (2009) and were measured on a scale from “1 = strongly disagree” to “7 = strongly agree”. Two items were reversed coded

The last mediating variable, perceived innovation ability, refers to the ability of the firm to generate new innovative products (Schreier et al., 2012). To measure this construct the items from Schreier et al. (2012) were adapted. Two of the items were reversed coded. The first question asked: What do you think about the firm’s innovation ability? I think this company’s ability to innovate is: was measured on a 7-point Likert scale from: “1 = not very high to 7 = very high”, “1 = not very strong to 7 = very strong” and “1 = not very excellent to 7 = very excellent”. In addition four extra question were asked which were measured on a 7 – point Likert scale from “1 = strongly disagree to 7 = strongly agree”.

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27 3.2.3 Moderating variables

Consumer competences and brand equity were expected to moderate the relationship between the independent and dependent variable. Consumer competences are the domain-specific knowledge and creativity-relevant processing skills a consumers owns (Füller et al., 2009). To measure this construct the items from Füller et al. (2009) were adapted. Two items were reversed coded. Consumer competences were divided into three different constructs: innovation task motivation, creative cognitive style and domain specific skills. All the items except two of domain specific skills were measured on a 7-point Likert scale from “1 = strongly disagree to 7 = strongly agree”. The items ‘How would you rate your skills to

contribute to (virtual) new product/service developments, compared to a professional product developer?’ and ‘How would you rate your skills to contribute to (virtual) new product developments, compared to the leisure activity you are best at?’ were measured on a 10-point Likert scale from “0 = your skills do not contribute to new product/service development to 10 = your skills do contribute to new product/service development”. These last two were

converted to a 7-point Likert scale before the results were analyzed.

The second moderating variable, brand equity, refers to the added value of the brand perceived by the consumer measured in brand loyalty, perceived quality, brand awareness, brand image and brand associations (Belén del Río et al., 2001; Hong-bumm Kim et al., 2003; Lassar et al., 1995). These items were adapted from Lassar, Mittal, & Sharma (1995). Four of the items were reversed coded. All the items were measured on a 7-point liker scale from “1 = strongly disagree to 7 = strongly agree”.

3.2.4 Control variables

The results of this study are controlled by four control variables. Gender, age,

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28 the survey, since it was possible that these variables would have an influence on the expected relationships. By adding them, the unexpected effects would be noticed.

3.3 Research design

For this study a cross-sectional research design was chosen. The data was collected by quantitative method, an online survey, created with Qualtrics software. The survey was distributed through social media and the administration started on the 22nd of April 2015. The survey was closed on the 9th of June 2015. The Statistical software Package for Social

Sciences (SPSS) was used to analyze the data. After recoding, the reliability scales,

descriptive statistics, the skewness, kurtosis and normality tests were computed for each scale. All the constructs were normally distributed, except consumer orientation and purchase

intention. Both constructs were moderately negative skewed (Table 1). Relatively high scores were obtained on both of the constructs, which was expected. It was expected that when people are involved in crowdsourcing they must perceive a high value in consumer orientation, since they are closely related to the company. In addition, the absence of a normal distribution of purchase intention can be explained by the fact that people who have participated in a crowdsourcing project feel connected to the product and want to buy the product or service. Hereafter the reliability scales and descriptive statistics were computed, shown in Table 2. All the constructs had a high level of reliability.

To test the direct effects and the hypothesized mediating and moderating effect between the variables, a regression analyses was performed. A hierarchical regression was used to test the direct effects. The regression analysis was performed for the dependent variable purchase intention. In step 1, the control variables, gender, age, nationality and education were entered. In step 2, brand equity and the consumer competences were entered into the model. In the final step the independent variable participation involvement and the

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29 mediating variables (perceived innovation ability, perceived consumer benefits and perceived consumer orientation) were entered into the model.

To test the mediating effect of perceived consumer orientation, perceived consumer benefits and perceived innovation ability, and the moderating effect of consumer

competences, and brand equity a regression analysis was performed with the Process SPSS macro of Hayes (2012). The default of 1000 bootstrap resamples was used on a confidence interval of 90 percent (Hayes, 2012). For the mediation effects model 4 of this macro was used. This model showed the results of the indirect effect of the mediators in relationship to participation involvement in crowdsourcing and the dependent variable consumers’ purchase intention. To examine the moderating effect of brand equity and consumer competences model 1 was used. In both analyses an alpha level of 0.10 was used.

Table 1 - Results normality distribution each scale

Variables N Skewness Kurtosis

Participation involvement 82 -.07 -.47 Perceived innovation ability 82 -.33 .27 Perceived consumer orientation 82 -.13 -.43 Perceived consumer benefits 82 -.85 1.44

Brand equity 82 -.36 .25

Consumer competences 82 -.22 -.77

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30

4. Results

In this chapter the results of the study are described. First, the description of the correlation analysis is given. Second, the results of the direct effect are showed. Hereafter, the mediating effects is outlined. Last, the moderating effect is explained.

4.1 Correlation analysis

In Table 2, the means, standard deviations and the correlations are exhibited. The table shows that participation involvement is positively correlated to the dependent variable

purchase intention (r = 0.22, p < 0.01). This indicates that there is a potential direct

relationship between these two variables. In addition consumers’ participation involvement is positively correlated to perceived innovation ability (r = 0.42, p < 0.01), perceived consumer orientation (r = 0.37. p < 0.01), and perceived consumer benefits (r = 0.70, p < 0.01). The latter being strongly positively correlated. Furthermore, perceived innovation ability (r = 0.43, p < 0.01), perceived consumers orientation (r = 0.56, p < 0.01), and perceived consumer benefits (r = 0.34, p < 0.01) are positively correlated with purchase intention. This indicates that there could be potential positive mediation effects.

The moderators are correlated with most of the variables. Brand equity and consumers competences are both positively correlated with the independent variable participation

involvement (r = 0.35, p < 0.01; r = 48, p < 0.01) and with the dependent variable purchase intention (r = 0.69, p < 0.01; r = 0.20, p < 0.10). Furthermore, brand equity is positively correlated with perceived innovation ability (r = 0.54, p < 0.01), with perceived consumer orientation (r = 0.69, p < 0.01), and with perceived consumer benefits (r = 0.39, p < 0.01). Consumer competences is positively correlated with perceived innovation ability (r = 0.34, p, 0.05), perceived consumer benefits (r = 0.44, p < 0.01), and with brand equity (r = 0.23, p < 0.05).

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31 Only the variables participation involvement and perceived consumer benefits are negatively correlated with the control variable age (r = -0.20, p < 0.10; r = -0.21, p < 0.10). Participation involvement is positively correlated to the control variables nationality and education (r = 0.32, p < 0.10; r = 0.20, p< 0.10). In addition, perceived consumer orientation is positively correlated to nationality (r = 0.26, p < 0.05) as well. Furthermore, perceived consumer benefits are positively correlated to nationality and education (r = 0.23, p < 0.05; r = 0.27, p < 0.05).

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32

Table 2 - Means, Standard Deviations, Correlations and Reliabilities

Variables

Number

of items M SD 1 2 3 4 5 6 7 8 9 10 11

1. Age 1 24.41 6.76

-2. Gender (0 = male, 1 = female) 1 .52 .50 .02

-3. Nationality 1 1.35 1.27 -.03 .19*

-4. Education 1 6.82 1.08 -.02 .25** .17

-5. Participation involvement 5 4.31 1.23 -.20* .07 .32*** .20* (.82)

6. Perceived innovation ability 10 5.03 .87 -.08 .14 .09 .03 .42*** (.84)

7. Perceived consumer orientation 6 5.29 .87 -.07 .12 .26** .11 .37*** .48*** (.74)

8. Perceived consumer benefits 14 4.62 .97 -.21* .14 .23** .27** .70*** .47*** .44*** (.92)

9. Brand equity 14 5.12 .72 .07 .11 .11 -.09 .35*** .54*** .69*** .39*** (.81)

10. Consumer competences 9 4.88 .81 .14 .04 .17 .13 .48*** .34** .15 .44*** .23** (.80)

11. Purchase intention 5 5.33 .86 -.04 .18 .16 .07 .22** .43*** .56*** .34*** .69*** .20* (.84) Note: N = 82. Reliabilities are reported along the diagonal

* Correlation is significant at the 0.10 level (2-tailed) ** Correlation is significant at the 0.05 level (2-tailed) *** Correlation is significant at the 0.01 level (2-tailed)

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33 4.2 Direct effects

In the first hypothesis the direct relationship between consumer participation involvement and purchase intention is described. To test this hypothesis a hierarchical multiple regression analysis is performed, see Table 3. In the first step four predictors were entered: age, gender, nationality and education. This model is statistically not significant F (4, 75) = 0.89; p > 0.10, which indicates that these predictors do not significantly explain the variance in purchase intention. Hereafter in step two the moderators, brand equity and consumer competences were entered into the model. The total variance explained by this model as a whole is 52.4% F (6, 73) = 13.38; p < 0.01. The introduction of brand equity and consumer competences explains an additional 47.9% variance in purchase intention after controlling for age, gender, nationality and education (ΔR2 = 0.48; F (2, 73) = 36.67; p < 0.01). In the final step, step 3, the variables participation involvement, perceived innovation ability, perceived consumer benefits, and perceived consumer orientation were entered into the model. This model is as well statistically significant F (10, 69) = 8.29; p < 0.01. The total variance explained by this model is 54.6%. An additional 2.2% variance in purchase intention is explained by adding these variables after controlling for age gender, nationality and

education (ΔR2 = 0.02; F (4, 69) = 0.83; p > 0.10).

In this final model two out of ten predictor variables are statistically significant, with brand equity (β = 0.64, p < 0.01) and education (β = 0.15, p < 0.10). Since this final model had a R2 of 0.55 (p > 0.10), which is not significant, it can be concluded that brand equity and education are significant predictors of variance. However, the second model has a R2 of 0.52 (p < 0.01). In this model only brand equity is significant (β = 0.70, p < 0.01). Thus, it can be concluded that brand equity is a significant predictor of the variance of purchase intention. Unfortunately, since there is no significant result between the predictor participation involvement and purchase intention, H1 is rejected.

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34

Table 3 - Regression analysis for Purchase Intention

R R² ∆R² Purchase intention Variables B SE ß t Step 1 .21 .05 Gender .24 .20 .14 1.22 Age -.01 .01 -.05 -.48 Nationality .08 .12 .07 .63 Education .36 .41 .10 .88 Step 2 .72 .52*** .49 Gender .12 .14 .07 .87 Age -.01 .01 -.11 -1.27 Nationality .04 .09 .04 .47 Education .49 .30 .14 1.65 Brand equity .85 .10 .70*** 8.30 Consumer competences .01 .09 .01 .14 Step 3 .74 .55 .48 Gender .10 .14 .06 .72 Age -.02 .01 -.13 -1.41 Nationality .05 .09 .04 .51 Education .53 .30 .15* 1.79 Brand equity .78 .15 .64*** 5.24 Consumer competences .07 .11 .07 .66

Perceived innovation ability .03 .10 .03 .27

Perceived consumer orientation .10 .12 .10 .85

Perceived consumer benefits .06 .11 .07 .54

Participation involvement -.14 .09 -.20 -1.58

Note: N = 82, Statistical significance; * p<0.10, ** p<0.05, *** p<0.01.

4.3 Mediation effects

In hypotheses 2, 3 and 4 it is proposed that perceived innovation ability, perceived consumer benefit and perceived consumer orientation would mediate the relationship between participation involvement and purchase intention. Process macro of Hayes (2012) was used to examine these relationships, see Table 4 - Mediation effects.

Firstly, the mediation effect of perceived innovation ability is examined in hypothesis 2. The results show that hypothesis 2a is supported, since the relationship of participation

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35 involvement on perceived innovation ability had a bootstrap confidence interval of [0.18, 0.42]. This indicates that there is a significant positive relationship (B = 0.30, p < 0.01). In addition, the hypothesis 2b, the relationship between perceived innovation ability and purchase intention is supported as well (B = 0.40, BCa90 = [0.22, 0.58], p < 0.01). The total indirect effect of perceived innovation ability is significant (R2 = 0.48; p < 0.01, B = 0.12, BCa90 = [0.07, 0.20]), whereas the direct relationship between participation involvement and purchase intention is not significant (B = 0.04, BCa90 = [-0.09, 0.17], p > 0.10). It can be concluded that hypothesis 2 is supported and that perceived innovation ability fully mediates the relationship between participation involvement and purchase intention.

Secondly, the mediating effect of perceived consumer orientation is examined in hypothesis 3. The direct effect of participation involvement on perceived consumer orientation is statistically significant (B = 0.26, BCa90 = [0.13, 0.38], p < 0.01), which indicates that hypothesis 3a is supported. The direct of perceived consumer orientation on purchase intention is proven to be significant as well (B = 0.54, BCa90 = [0.38, 0.71], p < 0.01), thus hypothesis 3b is supported. The total indirect effect of perceived consumer

orientation is significant (R2 = 0.31; p < 0.01, B = 0.14, BCa90 = [0.08, 0.23]). Since the direct relationship between participation involvement and purchase intention is not significant (B = 0.01, BCa90 = [-0.10, 0.13], p > 0.10), it can be concluded that perceived consumer orientation fully mediates the relationship between the two variables as well and thereby supports

hypothesis 3.

Lastly, it was predicted that perceived consumer benefits would mediate the

relationship between participation involvement and purchase intention in hypothesis 4. The results show that there is a statistically significant direct effect between participation

involvement and perceived consumer benefits (B = 0.56, BCa90 = [0.45, 0.66, p < 0.01), thus hypothesis 4a is supported. There is as well a statistically significant direct relationship

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36 between perceived consumer benefits and purchase intention (B = 0.32, BCa90 = [0.10, 0.54, p < 0.01), which supports hypothesis 4b. The total indirect effect of perceived consumer

benefits is significant (R2 = 0.12; p < 0.01, B = 0.18, BCa90 = [0.03, 0.34]). However, the direct effect of participation involvement on purchase intention is not significant (B = -0.02, BCa90 = [-0.20, 0.15], p > 0.10), which again indicates that hypothesis 4 is supported and that the relationship between the two variables is fully mediated by perceived consumer benefits.

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Table 4 - Mediation effects

Purchase intention BCa 90%

Variable R² B SE B t Lower Upper

Perceived innovation ability .48***

Direct effect of participation involvement on perceived innovation ability .30 .07 4.15*** .18 .42 Direct effect of perceived innovation ability on purchase intention .40 .11 3.61*** .22 .58 Total indirect effect of participation involvement on purchase intention .12 .03 .07 .20 Direct effect of participation involvement on purchase intention .04 .07 .48 -.09 .17

Perceived consumer orientation .31***

Direct effect of participation involvement on perceived consumer orientation .26 .07 3.57*** .13 .38 Direct effect of perceived consumer orientation on purchase intention .54 .10 5.44*** .38 .71 Total indirect effect of participation involvement on purchase intention .14 .05 .08 .23 Direct effect of participation involvement on purchase intention .01 .07 .20 -.10 .13

Perceived consumer benefits .12***

Direct effect of participation involvement on perceived consumer benefits .56 .06 8.85*** .45 .66 Direct effect of perceived consumer benefits on purchase intention .32 .13 2.45** .10 .54 Total indirect effect of participation involvement on purchase intention .18 .09 .03 .34 Direct effect of participation involvement on purchase intention -.02 .10 -.22 -.20 .15 Note: N = 82, Statistical significance; * p<0.10, ** p<0.05, *** p<0.01.

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38 4.4 Moderation effects

Consumer competences and brand equity are argued to have a moderating effect on the proposed relationships. These moderating effects are examined with the same Process Macro of Hayes (2012) as used to examine the mediating effect. In table Fout! Ongeldige

bladwijzerverwijzing.Table 6 Table 7 the moderating effect of consumer competences is

shown and in tableTable 8Table 9 the moderating effect of brand equity.

The results show that consumer competences do not moderate every relationship that was stated. All the models indicate a significant model (perceived innovation ability: R2 = 0.23, p < 0.01; perceived consumer orientation: R2 = 0.22, p < 0.01; perceived consumer benefits: R2 = 0.54, p < 0.01). However, the interaction effect of consumer competences on the relationship between participation involvement and a) perceived innovation ability and b) perceived

consumer benefits is not significant (perceived innovation ability: B = 0.07, BCa90 = [-0.08, 0.22], p > 0.10; perceived consumer benefits: (B = 0.09, BCa90 = [-0.04, 0.22], p > 0.10). This is also shown in the small and insignificant change of the R2 due to the interaction (both: ΔR2 = 0.01; p > 0.10). Thus, hypothesis 5a and 5c are rejected. The interaction effect of consumer competences on the relationship between participation involvement and perceived consumer benefits is statistically significant (B = 0.19, BCa90 = [0.04, 0.34], p < 0.05). This is supported by the significant change in R2 due to the interaction (ΔR2 = 0.05, p < 0.05). Thus, hypothesis 5b is supported. Thus, consumer competences only moderate the relationship between

participation involvement and consumer orientation.

The second expected moderator was brand equity. The first model shows that the moderating effect of brand equity on the relationship between perceived innovation ability on purchase intention is significant (R2 = 0.52, p < 0.01). However the interaction effect of brand equity is not statistically significant (B = 0.06, BCa90 = [-0.14, 0.26], p > 0.10). As well, this is shown by the little change in R2 due to the interaction, which is not significant (ΔR2 = 0.00, p >

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39 0.10). Thus, hypothesis 6a is rejected. The second model displays the moderating effect of brand equity on the relationship between perceived consumer orientation on purchase intention. The model is significant (R2 = 0.54, p < 0.01). However, the interaction effect of brand equity is not statistically significant (B = 0.14, BCa90 = [-0.04, 0.31], p > 0.10), which is also shown in the small change in R2 due to the interaction (ΔR2 = 0.01, p > 0.10). Thus, hypothesis 6b is rejected. The last hypothesis is about the moderation effect of brand equity on the relationship between consumer benefits and the purchase intention. The model is significant (R2 = 0.53, p < 0.01). However, the interaction effect of brand equity is not statistically significant (B = 0.05, BCa90 = [-0.09, 0.20], p > 0.10). This is supported by the non significant change in R2 due to the interaction (ΔR2

= 0.00, p > 0.10). Thus, hypothesis 6c is rejected. Unlike expected this study did not provided proof that brand equity has a moderating effect on the purchase intention of consumers.

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40

Table 5 - Moderating effect of Consumer Competences on the relationship between Participation Involvement and Perceived Innovation Ability

Perceived innovation ability BCa 90%

Variable R² ∆R² B SE B t Lower Upper

Interaction variable consumer competences .23*** .01

Participation involvement -.14 .47 -.30 -.93 .65

Consumer competences -.09 .38 -.24 -.72 .54

Participation involvement x Consumer

competences .07 .09 .82 -.08 .22 Control Variables Age -.00 .01 -.31 -.03 .02 Gender .23 .18 1.24 -.08 .53 Nationality -.05 .08 -.08 -.18 .07 Education .01 .40 .02 -.65 .67

Note: N = 82, Statistical significance; * p<0.10, ** p<0.05, *** p<0.01.

Table 6 - Moderating effect of Consumer Competences on the relationship between Participation Involvement and Perceived Consumer Orientation

Perceived consumer orientation BCa 90%

Variable R² ∆R² B SE B t Lower Upper

Interaction variable consumer competences .22*** .05**

Participation involvement -.73 .48 -1.54 -1.53 .06

Consumer competences -.79 .38 -2.07** -1.43 -.15

Participation involvement x Consumer

competences .19 .09 2.10** .04 .34 Control Variables Age .00 .01 .32 -.02 .03 Gender .14 .18 .75 -.17 .44 Nationality .09 .08 1.13 -.04 .21 Education -.03 .40 -.08 -.70 .63

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41

Table 7 - Moderating effect of Consumer Competences on the relationship between Participation Involvement and Perceived Consumer Benefits

Perceived consumer benefits BCa 90%

Variable R² ∆R² B SE B t Lower Upper

Interaction variable consumer competences .54*** .01

Participation involvement .02 .41 .05 -.66 .71

Consumer competences -.15 .33 -.44 -.69 .40

Participation involvement x Consumer

competences .09 .08 1.12 -.04 .22 Control Variables Age -.02 .01 -1.30 -.04 .00 Gender .18 .16 1.12 -.09 .33 Nationality -.02 .07 -.27 -.13 .09 Education .18 .34 .53 -.39 .76

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42

Table 8 - Moderating effect of Brand Equity on the relationship between Perceived Innovation Ability & Perceived Consumer Orientation and Purchase Intention

Purchase intention BCa 90%

Variable R² ∆R² B SE B t Lower Upper

Interaction variable brand equity .52*** .00

Perceived innovation ability -.29 .65 -.44 -1.36 .79

Brand equity .52 .61 .85 .50 1.54

Perceived innovation ability x Brand equity .06 .12 .49 -.14 .26

Control Variables

Age -.01 .01 -1.21 -.03 .00

Gender .12 .14 .80 -.12 .36

Nationality .04 .06 .65 -.06 .13

Education .50 .30 1.68* .00 .99

Interaction variable brand equity .54*** .01

Perceived consumer orientation -.54 .51 -1.07 -1.39 .30

Brand equity .01 .58 .01 -.96 .97

Perceived consumer orientation x Brand equity .14 .10 1.31 -.04 .31

Control Variables

Age -.01 .01 -1.00 -.03 .01

Gender .13 .14 .94 -.10 .36

Nationality .01 .06 .21 -.08 .11

Education .47 .29 1.64 -.01 .96

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Table 9- Moderating effect of Brand equity on the relationship between Perceived Consumer Benefits and Purchase Intention

Purchase intention BCa 90%

Variable R² ∆R² B SE B t Lower Upper

Interaction variable brand equity .53*** .00

Perceived consumer benefits -.28 .47 -.59 -1.05 .50

Brand equity .59 .38 1.57 -.04 1.22

Perceived consumer benefits x Brand equity .05 .09 .63 -.09 .20

Control Variables

Age -.01 .01 -.18 -.03 .01

Gender .12 .13 .81 -.12 .35

Nationality .04 .06 .69 -.06 .13

Education .50 .30 1.68* .00 1.00

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