Identifying the impact of motivational drivers that stimulate an
individual’s intention to voluntary participate in
online idea generation initiatives
Student name: Jairo Timmermans
Student number: 10657584
Date: 29-06-2015
Education: M.Sc. Business Administration – Strategy track
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Statement of originality
This document is written by Jairo Timmermans who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of work, not for contents.
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Table of contents
Acknowledgements 7
Abstract 8
1. Introduction 9
2. Literature review and hypotheses development 14
2.1 Co-creation 14
2.2 Collaborative innovation 15
2.3 Online idea generation by crowdsourcing 16
2.4 Intention to participate 18
2.5 Motivational drivers 19
2.5.1. Uses and Gratification framework: perceived benefits 20
2.5.1.1 Learning Benefits 21
2.5.1.2 Social Integrative Benefits. 22
2.5.1.3 Personal Integrative Benefits. 22
2.5.1.4 Hedonic Integrative Benefits. 23
2.5.1.5 Direct compensation benefits 23
2.6 Theory of Planned behaviour (TPB) 24
2.6.1 Perceived Behavioural Control - Self-efficacy 25 2.6.2 Self-efficacy moderated by direct compensation 26
2.6.3 Attitude 27
2.6.3.1 Trust 27
2.6.3.2 Attitude as mediator between trust and intention 28 to participate
2.6.4 Subjective norm 29
2.6.4.1 Community identification 29
2.7 Main research question, hypotheses, and conceptual model 30
3. Methodology 33
3.1 Research design 33
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3.3 eYeka, InnoCentive, Facebook 34
3.3.1 InnoCentive 34
3.3.2 eYeka 35
3.4 Measures and survey outline 36
3.4.1 Intention to participate 36 3.4.2 Perceived benefits 36 3.4.3 Self-efficacy 37 3.4.4 Trust 38 3.4.5 Attitude 38 3.4.6 Subjective norm 38 3.4.7 Community Identification 38 3.4.8 Demographic variables 39 3.5 Survey outline 39 3.6 Statistical procedure 40
4. Results and Analysis 41
4.1 Sample characteristics 41
4.2 Cross-tabulations 43
4.2.1 Gender - Highest education level 43
4.2.2 Current occupation – Gender 44
4.2.3 Highest education level - Current occupation 44
4.3 Data screening 45
4.3.1 Frequency distributions 45
4.3.2 Counter-indicative items 46
4.3.3 Outlier detection and removal 46
4.3.4 Descriptive statistics, normality, skewness, kurtosis 46
4.3.5 Inter-correlation of scale items 47
4.3.6 Internal validity and reliability 47
4.3.7 Checks for multicollinearity 48
4.4 Hypothesis testing 51
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4.4.2 Effect of perceived benefits on intention to participate 52 4.4.3 Effect of Subjective norm, Self-efficacy, Trust and Attitude 53
on intention to participate
4.4.4 Moderation Direct compensation between self-efficacy 53
and intention to participate 54
4.4.5 Moderation effect of Community identity on relation 54 Subjective norm and intention to participate
4.4.6 Mediation effect of Attitude between trust and intention to 55 participate
4.5 Additional testing - Direct compensation as a moderator on relation 55 between uses and gratification framework and intention to participate
4.5.1 Moderation Direct compensation between Learning and 56 intention to participate
4.5.2 Moderation Direct compensation between Social integrative 57 and intention to participate
4.5.3 Moderation Direct compensation between Personal integrative 57 and intention to participate
4.5.4 Moderation Direct compensation between Hedonic integrative 58 and intention to participate
4.6 Summary of the hypotheses test results 60
5. Discussion 61
5.1 Impact of perceived benefits of intention to participate 61 5.2 Additional testing - Direct compensation as a moderator 62 5.3 Impact of Theory of Planned behaviour on intention to participate 62 5.4 Impact of Self-efficacy on intention to participate 63 5.5 Impact of trust and attitude on intention to participate 64
6. Limitations and implications 66
6.1 Theoretical and managerial implications 67
7. Conclusion and avenues for future research 69
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9. Appendices 78
Appendix A – Survey invitation 78
Appendix B – Complete survey 79
Appendix C – Frequency distribution per item 86
Appendix D – Descriptives per item 89
Appendix E - Normality testing and Normal Q-Q plots per construct 90 Appendix F – Overview results hierarchical regression 94 Appendix G - Results Moderation and Mediation tests 95
Appendix H - Additional testing 97
Figures
Figure 1 Outside-in process, Chesbrough (2003) 10
Figure 2 Conceptual model predicting intention to participate 32 Figure 3 Moderation effect Direct compensation on relation Self-efficacy 53 Figure 4 Moderation effect Community identification on relation Subjective norm 54 Figure 5 Moderation effect Direct compensation on relation Learning 56 Figure 6 Moderation effect Direct compensation on relation Social integrative 57 Figure 7 Moderation effect Direct compensation on relation Personal integrative 58 Figure 8 Moderation effect Direct compensation on relation Hedonic integrative 59 Tables
Table 1 Gender profile 41
Table 2 Age profile 42
Table 3 Highest education level obtained 42
Table 4 Current occupation of respondents 43
Table 5 Cross tabulation Highest education level - Gender 44
Table 6 Cross tabulation Current occupation - Gender 44
Table 7 Cross tabulation Highest education level – Current occupation 45
Table 8 Correlation matrix all variables 50
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Acknowledgements
Several individuals helped me set up and carry out this study, therefore my gratitude goes out to them. First, I would like to thank my supervisor Carsten Gelhard for his guidance throughout the process. He helped to give direction to the foundation of the research and provided valuable feedback where needed. Second, I would like to thank all respondents that were willing to take the effort and help me collect data by filling out my survey, without this my research would not have been possible.
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Abstract
Online idea generation initiatives are a form of crowdsourcing in which a firm outsources the task of coming up with innovative ideas to a large group of individuals via a virtual channel. Crowdsourcing is an aspect of co-creation used by firms to exploit external knowledge and skills with the aim of gaining a competitive advantage. This study aims to identify motivational drivers for individuals to engage in online idea generation initiatives and analyse the influence of such drivers on an individual’s intention to participate. Motivational drivers were derived from the literature and combined in a conceptual model. Main variables stem from the uses and gratification framework and the theory of planned behaviour. In addition, the incentive ‘direct compensation’ was added and the influence of trust was included into the model. Findings show that ‘learning’, ‘personal integrative’, ‘hedonic integrative’ and ‘attitude’ are the main predictors of an individual’s intention to participate in online idea generation initiatives. The results also show that ‘trust’ has an influence on ‘attitude’, meaning that trustworthiness of firms has an indirect implication on an individual’s intention to engage in their online idea generation efforts. Further, the study showed that although in the model ‘direct compensation’ was no significant predictor of intention to participate, it does play a role in the equation. ‘Direct compensation’ moderates the relationship between the motivational drivers of perceived benefits and ‘self-efficacy’ and intention to participate in online idea generation initiatives.
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1. Introduction
"I am sure there are a lot of things that I can't imagine, but our customers can imagine. A company of this size is not going to be about a couple of people coming up with ideas. It's going to be about millions of people and harnessing the power of those ideas" – Dell CEO Michael Dell.
Consumers are getting more and more involved in the creation of goods and/or services by firms. More than ever, they try to exercise their influence in each part of the business industry. This due to dissatisfaction with available choices and because new tools and technology allows them to do so. In turn, consumer and firm interaction is becoming more important and leading to value co-creation (Prahalad, 2004). The core idea of co-co-creation is engaging people to create valuable experiences together (Leavy, 2012). Looking at co-creation from a firm’s perspective entails that firms should not only rely on their own resources, but also be open to inputs from beyond the firms’ boarders. By doing this it will enable firms to learn and get new ideas for design, engineering, and manufacturing (Prahalad, 2004). Additionally, employees will be able to gain a better understanding of consumer aspirations, desires, motivations and behaviours. Meaning that in strategy design firms should be focussing on “engage and discover” not “command and cascade” (Christensen et al., 2005; See-To, 2014). Managers should be open to outside innovation and be aware of the fact that previous research found an effect of co-creation on purchase intentions (Christensen et al., 2005). This effect implied that the way and level of involvement of customers in creating value has an impact on the decision to buy or not to buy. Thus, firms should engage in co-creation efforts because they otherwise might miss out on valuable information and opportunities to gain a competitive advantage. The concept of co-creation is an outside–in process (figure 1), also referred to as open innovation, as it starts from the customer’s value-creating process instead of from the firm itself (Payne, 2008).
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Figure 1 Outside-in process, Chesbrough (2003)
‘Not all the smart people work for us. We need to work with smart people inside and outside our company’ (Chesbrough, 2003).
In order for firms to be competitive they are dependent on innovation (Shawney et al. 2005).
Grassmann (2004) explains co-creation as the enrichment of a company’s own knowledge base through the
integration of suppliers, customers, and external knowledge sourcing to increase a company’s
innovativeness. The importance of online co-creation as a source of ideas for innovation is also recognized
in multiple studies (Gebauer et al. 2012; Tanev et al. 2011; Prandelli et al. 2006; von Hippel 2005).
Additionally, co-creation can be seen as an innovative tool that can be applied in line with the dynamic
capabilities view by Grant (1996): to exploit external competences and integrate them with internal
competences in order to be able to address changing environments rapidly. In fast changing markets, firms
that are more capable of gaining, processing and exploiting knowledge from parties outside the firm can
gain a competitive advantage over firms that are less capable of doing so. In other words, co-creation offers a lot of opportunities for firms in the field of innovation and competitiveness. On foresight, it is therefore
more significant for firms to engage in innovation through co-creation than for consumers as a firm’s
benefits from co-creation are obvious: profit and competitive advantage. Consumers benefits are less
11 into it if he or she can also wait for someone else to engage in co-creation and then just buy the product? In
order for firms to maximize their gains from engaging in co-creation and finding the best way to combine
the co-creation building blocks (DART-model; Prahalad, 2004) it is important to understand how consumers
can be motivated to participate in co-creation initiatives. Little research has been done so far to gain insight
in the motivation of customers to get involved in co-creation efforts.
Roberts et al. (2013) delved into the subject and argue that motivations seem to be different depending on the type of co-creation efforts. For example, egocentric motives influence innovation independent of the firm, altruistic motives drive innovation as part of a community and opportunity stimulates innovation directly in collaboration with the firm. However, they recognized limitations in their research in terms of generalizability. Roberts et al. therefore suggest that empirical work is needed regarding value co-creation to further our understanding of the consumer’s motivation to participate in those activities. Study by Füller (2008) suggests that financial, social, technical, and psychological factors all play a role in the ability and willingness of consumers to engage productively in the co-creation process. Stock et al. (2014) adds to this that when individual consumers develop products for their own use, they may expect to be rewarded by the use value of what they are creating. In addition, consumers may also expect to be rewarded intrinsically by factors like fun and learning experience derived from creating it. Thus from previous research one can derive that consumers are motivated extrinsically, but also have intrinsic needs. It is up to the firms to establish such an environment that stimulates consumers to involve in the co-creation process and thus allows firms to access their knowledge.
An increasing number of firms are anticipating on co-creation and outside innovation via the internet as they are hosting virtual customer environments to involve their customers in product development (Nambisan, 2009). Zheng et al. (2011) suggests that firms can seek innovative
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external ideas and solutions to business tasks by initiating co-creation activities. Additionally, according to Stock et al. (2014) mechanisms such as contests and gamification might motivate consumers to co-create because of the prize rewards, and maybe at the same time it motivate consumers who are looking for intrinsic rewards such as fun and learning, the authors suggest future research should be done in this field. Additionally, study by Hoyer (2010) proposed future research in this subject by looking into the question: 'What incentives should the firm provide to spur customer input in co- creation?' This paper intends to fill that gap and contributes to the existing literature by using a quantitative approach and actually measuring motivation levels. Prior studies mainly performed explorative research, identifying motives for participation. This research main contribution is to bring together multiple existing theories and integrate them in the design of a new conceptual model. This in order to create a more complete understanding of the motivational drivers for behavioural intention to engage in co-creation, in the context of online idea generation. The results might shed light on how firms should design an environment that motivates consumers to engage in their co-creation practices.
Research question: What are the main motivational drivers that stimulate individuals to voluntary participate in online idea generation initiatives, and to what extent do these drivers impact an
individual’s intention to participate in online idea generation initiatives?
The paper is structured as follows. Chapter two contains a literature review that consists of relevant existing literature regarding this study. By discussing the literature, motivational drivers will be identified and described which will be used as constructs for this study. In addition, the hypothesized relationships between constructs will be proposed. Chapter three provides an overview and explanation of the used methodology, which includes the data collection method, sampling frame, measurements of constructs and the statistical procedure. Chapter four discusses
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the research results, thereafter a discussion of those results is provided in chapter five. Chapter six will finalize the study with the conclusions based on the study findings and suggestions for future research.
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2. Literature review and hypotheses development
The literature review starts with an insight in the phenomenon of co-creation and zooms in on the aspect online idea generation thereafter. Next, motivational drivers and predictors of behavioural intention will be discussed which includes hypotheses formulation. Finally, an overview of the theoretical framework is presented, consisting this paper’s research question, hypotheses, and conceptual model of the hypothesized relationships.
2.1 Co-creation
Value creation originally was a one-way street which happened inside the firm, consumers where outside the firm. The distinct role of the firm was to provide production, the consumer on the other hand for filled the role of consumption. However these roles became less distinct over time and moved towards a new paradigm, co-creation. Co-creation regards the joint creation of value by the firm and the customer (Prahalad, 2004). Lusch et al. (2007) suggest that firms require an absorptive competence in order to innovate their value propositions or offered services. In other words, firms must be able to capture and understand important external trends and knowledge. Co-creation is about allowing customers to co-construct a service or product and about treating the customer as a contributor with knowledge and skills, by having an active dialogue with firms.
“Today the customer is in charge and whoever is best at putting the customer in charge makes all the money.” (Stephen F. Quinn, Senior Vice President Wal-Mart, quoted in Elliott, 2006)
The aspect dialogue is important in the co-creation view. In terms that markets can be viewed as a set of conversations between the customer and the firm (Levine, Locke, Searls, & Weinberger, 2001). However, consumers and firms should be able to access the same information to make a dialogue functional. Therefore transparency is required. In turn, this will allow the
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consumer to assess the risk or benefits of engaging in co-creation or not (Prahalad, 2004). The concept co-creation has captured the imagination of marketing and management professionals and scholars. Zwick et al. (2008) argue that the true meaning of co-creation is administering consumption in ways that allow for the continuous emergence and exploitation of creative and valuable forms of consumer labour. Thus the smartest marketers should let go of Philip Kotler's 'Four Ps' (1989) and focus on the provision of ambiances that set consumers free to produce and share technical, social, and cultural knowledge (Zwick, 2008), however the question for firms arises how to provide such a motivating environment?
2.2 Collaborative innovation
For companies there is one context in which consumer co-creation is becoming more and more important: the area of innovation and new product development. This part of co-creation is also referred to as user-innovation, open innovation and collaborative innovation. Research has shown that for an innovation or new product development to be successful, companies need an in-depth understanding of the needs and wishes of consumers (Hauser, Tellis, and Griffin 2006). Additionally, consumers have the ability and the willingness to provide ideas for new goods or services, potentially innovative for existing offerings (Ernst, Hoyer, Krafft, and Soll 2010). Thus, when consumers are actively involved in the innovation/new product development process of companies, these needs will be known and can be integrated in the new product development. In turn, it will be more likely that new product ideas are generated which are have a higher likelihood of new product success (Hoyer, 2010). Academics started to emphasize that firms should be open to outside innovation, as they recognize cooperation with externals to be core in order to increase innovativeness and reduce time to market (Rigby and Zook, 2002; Christensen et al., 2005; Enkel,
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2009). Baldwin and von Hippel (2011) even suggest co-creation in terms of consumer innovation increasingly compete with and might even replace producer innovation in many facets of the business industry. Taken this into account it is valuable for companies to understand how to provide an environment that attracts and motivates consumers to engage in innovative co-creation practices. A platform that seems to have unlimited possibilities in our current world is the internet. It allows companies to engage customers and create an ongoing dialogue to access and absorb customer knowledge (Sawhney, 2005).
2.3 Online idea generation by crowdsourcing
Crowdsourcing is a form of co-creation via an online distributed problem-solving and production model. In the article of Brabham (2008) crowdsourcing is defined as: “the act of a company or institution taking a function once performed by employees and outsourcing it to an undefined (and generally large) network of people in the form of an open call. This can take the form of peer-production, but is also often undertaken by sole individuals.” Essential in this process is the use of the open call concept combined with the large network of potential labourers. In this study the focus will be on the crowdsourcing form: idea generation in a virtual environment. Once idea generation was restricted to and performed by employees, now outsourced to a large network of people. Online idea generation initiatives is any kind of virtual action taken by a firm to access the knowledge and skills of individuals that are not part of the firm, in order to generate new ideas for problem solving or innovation creation. A common used tool set up by firms is an ideas competition. The firm is the organizer of such an initiative and sends out an invitation to a general public or targeted group to submit contributions to a certain challenge within a predefined period of time. The submitted ideas will then be reviewed by a committee of the firm and one or more
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winning ideas will be selected (Ebner 2008, Vallerand, 1998). In other words, online idea competitions can be used in the innovation process of firms in order to expand the source of potential new ideas. The business model has shifted from one designer, one client, and one solution towards an environment where problems are taken up everywhere and by anyone, solutions are developed and tested by the individuals around the world (Mau, 2004). Ideas competitions usually bring along a competitive character which encourages participants to produce an innovative winning idea. This aspect of competition can be seen as beneficial for the development of innovations (von Hayek, 1971). A form of competition can be a contest, which is an increasingly popular mechanism for encouraging innovation where participants are rewarded in form of a prize (Boudreau, 2011). Prizes are one of the oldest tools to define success, recognize effort and identify promising participants capable of achieving difficult tasks. However, there are some concerns in designing innovation contests. A central concern is how to design a contest in such a way that consumers will be motivated to take the effort and engage in the co-creation practice. This because consumers will only volunteer their time and talent if they believe co-creation to be rewarding (Füller, 2010). A better understanding is needed because firms providing co-creation platforms risk to generate little interest in participation and thus not enjoying the valuable consumer insights co-creation practices can deliver. Firms and their managers need to gain more insight in consumers’ expectations, this in turn to anticipate on consumers motivations to engage in co-creation practices and maximize consumer contributions. However, all the facilities and technology seems to be present, consumers need to be triggered to engage in the actual co-creation, hence the question arises: how can people be motivated or stimulated in their intention to participate?
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2.4 Intention to participate
Behavioural intention is an immediate determinant for actual behaviour according to the Theory of Planned Behaviour (Ajzen, 1991). Behavioural intention is a measure of the likelihood of an individual getting involved in a given behaviour (Ajzen and Fishbein, 1980). Three independent factors determine behavioural intention. The first is attitude towards the specific behaviour. Attitude concerns the degree to which an individual is favourable or unfavourable towards the behaviour (Ajzen, 1991). Subjective norm is the second determinant, referring to the perceived social pressure an individual copes with in the decision to engage in the behaviour. The third determinant of behavioural intention is perceived behavioural control which considers the degree of difficulty to perform the behaviour (Ajzen, 1991). The relative importance of each of the three factors is highly context dependent. For example, in a particular context only subjective norm has a significant impact on behavioural intention, however in another setting all three determinants have a significant impact. This means that all three determinants may contribute independently. Additionally, Ajzen (1991) argues that the stronger the behavioural intention, the more likely it is that the behaviour will be performed. This study will use behavioural intention in order predict an individuals planned behaviour of participating in online idea generation initiatives. In other words, applying the TPB to this study means that behavioural intention will take the role of the dependent variable, ‘intention to participate in online idea generation initiatives’. Examining behavioural intention can lead to a substantive prediction about actual engagement of individuals to engage in online idea generation initiatives.
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2.5 Motivational drivers
Psychological literature identifies two types of motivation to perform tasks or engage in activities, extrinsic and intrinsic (Davis, Bagozzi, and Warshaw, 1992; Deci and Ryan, 1985). Extrinsically motivated individuals engage in an activity in order to gain a desired consequence or avoiding an undesired one, so they are energized into action only when the action leads to those ends. Intrinsic motivated individuals engage in an activity because they find it interesting and gain spontaneous satisfaction from the activity itself (Gagné and Deci, 2005). Consumers differ in their skills to be able to contribute to innovation but also in their intention to engage in such activities (O’Hern and Rindfleisch 2009). Intention to participate can be influenced by offering intrinsic and/or extrinsic incentives. Extrinsic incentives could be monetary prizes or profit sharing, but customer engagement could also be rewarded by vouchers or gift cards (Brabham, 2008; Hoyer et al., 2010). Next to direct rewards, indirect rewards can influence motivation to engage in co-creation practices. For example, recognition gained from participation which might enable the participant to find employment in the future (Hoyer et al., 2010). Moreover, consumers might be motivated because of the opportunity of socializing through interaction and discussions between users and the company (Kohler et al., 2011). Intrinsic motives to participate could derive from interest in product or service improvement (Füller et al., 2010). In addition, learning might be a motivation as well as staying up-to-date with recent developments, trends, products and technology (McLure Wasko & Faraj, 2000). Furthermore, consumers could engage in co-creation practices simply because it is a form of pleasure, enjoyment and entertainment, because they can gain social contact or because it allows them to increase their reputation (Luo, 2002; Nambisan, 2009). On the other hand, consumers can also be demotivated to engage in co-creation or during the process of co-creation. For example, consumers that simply do not want to share knowledge, because they do
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not benefit from the profits made by the firm (Brabham, 2008). Next, the perceived benefits to the consumer might not out way the effort put into it (Colombo, Lucking, & Mcinnes, 2011). Other de-motivational aspects might be a lack of transparency by the firm or no clear defined challenges (Luo, 2002). One way or another, participants in online idea generation initiatives have been motivated to do so. A concept that explains internet behaviour, in this case participation in online idea generation initiatives, is the uses and gratifications framework. It explains the behaviour in terms of expected positive outcomes, or gratifications (La Rose, 2001).
2.5.1. Uses and Gratification framework: perceived benefits
There are four types of benefits that individuals can gain from media usage (in this case, from participating in online idea generation initiatives) according to the uses and gratification framework (Katz et al., 1974). First are cognitive benefits that relate to information acquisition and strengthening of the understanding of the environment. Second, the social integrative benefits that relate to strengthening consumer’s ties with relevant others. Third, the personal integrative benefits that relate to strengthening the credibility, status and confidence of the individual. Last, the hedonic benefits that strengthen aesthetic or pleasurable experiences (Katz et al., 1974, Nambisan, 2009). The framework is applied to Internet and other computer-mediated environments in multiple studies (e.g., Kaye and Johnson, 2002; Stafford et al., 2004, Nambisan, 2009). These studies show that the underlying categories of the uses and gratification framework are stable even though the specific nature of such benefits may depend on the context. The primary focus in this study is on customers’ perceived benefits of online idea generation initiatives and on the level to which these perceived benefits predict the intention to participate in such online idea generation initiatives. Therefore, the uses and gratification framework provides a useful theoretical foundation. However, the uses and gratification framework does not take into account rewards, financial nor
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financial. Nevertheless, such incentives in the form of ‘direct compensation’ are implemented by many firms in order to attract participants to their online idea generation initiatives. Brabham (2010) even suggests that the opportunity to make money is a key determinant of crowd usage of crowdsourcing applications. Therefore this study proposes an extension to the uses and gratification framework by including the perceived benefit: ‘direct compensation’. In this research the five benefit categories can be interpreted as follows.
2.5.1.1 Learning Benefits
The opportunity to learn is proven to be one of the key motivators in participating in crowdsourcing initiatives (Hertel, 2003). In this study ‘learning’ benefits are associated with product and process learning. This means gaining insight and a better understanding of the products and services, their underlying technologies and their usage. Additionally, the learning benefit is associated with opportunities for skill development. Personal skills, capabilities and knowledge are described as special forms of capital, otherwise referred to as human capital (Hars and Ou, 2001). Idea generation initiatives of firms can support an individual’s development of his or her human capital. This, by developing processes which take into account the individual’s capability to learn (Payne, 2008). Such processes could be learning from other participants by means of team work or learning from guidance by a mentor or coach (Leimeister, 2009). In turn, individuals might seek to enhance their human capital by means of engaging in an idea generation initiative that provides such opportunity.
H1: A greater perceived opportunity for ‘learning’ possibilities leads to a greater intention to participate in online idea generation co-creation initiatives.
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2.5.1.2 Social Integrative Benefits.
The social integrative context for online idea generation initiatives is defined by the participating customers and members of the hosting firm. Participants demonstrate their capabilities, skills and competence and in return they expect reactions and interactions with other participants and with representatives of the firm that hosts the initiative (Leimeister, 2009). The social benefits address the benefits gained from the social relationships that are built between the participating parties in the idea generation initiative. These relationships are beneficial to a participant as it creates a sense of belongingness and social identity (Kollock, 1999). Therefore this paper suggests that firms who provide idea generation initiatives with opportunities for interaction with the firm’s representatives or with fellow participants, will lead to a greater intention for individuals to participate.
H2: A greater perceived opportunity for ‘Social integrative’ possibilities leads to a greater intention to participate in online idea generation co-creation initiatives.
2.5.1.3 Personal Integrative Benefits.
In this study personal integrative benefits links to the achievement of reputation or status. Reputation, in this context, refers to the degree to which an individual sees opportunities to enhance their personal status through knowledge sharing (Hsu and Lin, 2008). The possibility to gain reputation is an important asset to individuals as it can leverage to achieve and maintain status within a collective (Jones et al., 1997). Previous study pointed out that reputation and status are found to be a motivator for content contributors (McLure-Wasko and Faraj, 2005). Online idea generation initiatives can serve as a means for individuals to show their product-related knowledge
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and problem- solving skills. The perception that knowledge contribution will allow for enhancement of an individual’s reputation towards peer participants and towards the host firm, may be an incentive for individuals to contribute their valuable, personal knowledge to others in an idea generation initiative.
H3: A greater perceived opportunity for ‘Personal integrative’ possibilities leads to a greater intention to participate in online idea generation co-creation initiatives.
2.5.1.4 Hedonic Integrative Benefits.
Nambisan (2009) argues that participants’ interactions with a co-creation system can be mentally stimulating, entertaining and a source of pleasure and enjoyment. In addition, pleasure can be derived from discussing the problem or challenge of in this case the idea generation initiative with one another (Muniz and O’Guinn, 2001). Kohler (2011) suggest that co-creation initiatives in a virtual world can be a source of enjoyment when they nurture playfulness and providing challenging tasks. Moreover, the problem solving that underlies much of the interactions in online idea generation initiatives might also be a source of mental or intellectual stimulation (Nambisan, 2009). Intentions to participate in idea generation initiatives might increase when such initiatives contain hedonic features.
H4: A greater perceived opportunity for ‘Hedonic integrative’ possibilities leads to a greater intention to participate in online idea generation co-creation initiatives.
2.5.1.5 Direct compensation benefits
In this context ‘direct compensation’ benefits are financial or non-financial rewards from participating in, and often winning, an idea generation initiative. Non-financial rewards can be
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vouchers, gifts or a position at the company that hosts the idea generation initiative. Lerner and Tirole (2000) argue that direct as well as delayed rewards may be the reasons why consumers engage in innovation activities. Brabham (2010) takes this even further and claims that the opportunity to make money or to win a non-monetary prize is a key determinant of crowd usage of crowdsourcing applications. Previous study also indicates that reward has been known to increase motivation (Cameron and Pierce, 1994). Additionally, when rewards are appropriate in their context they will attract new participants or stimulate already participating individuals to make even better contributions (Fuller, 2006). Therefore this study aims to apply rewards in the context of online idea generation and suggests that an individual’s intention to participate in online idea generation initiatives will increase when such an initiative provides opportunities to gain a financial or non-financial direct compensation.
H5: A greater perceived opportunity for ‘Hedonic integrative’ possibilities leads to a greater intention to participate in online idea generation co-creation initiatives.
By applying the uses and gratification framework in the context of this study and adding one additional antecedent, a set of five categories have been identified that may inform on an individual’s intention to participate in online idea generation initiatives.
2.6 Theory of Planned behaviour (TPB)
The uses and gratification framework sole focuses on perceived benefits to explain behavioural intentions. However, according to Ajzen (1975) and his theory of planned behaviour (TPB) there are other essential factors in explaining behavioural intention. This study suggests that the uses and gratification framework should be extended in order to grasp a more complete picture
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of behavioural intention to participate in online co-creation. Ajzen (1975) argues: “A behavioural intention measure will predict the performance of any voluntary act, unless intent changes prior to performance or unless the intention measure does not correspond to the behavioural criterion in terms of action, target, context, time-frame and/or specificity.” In other words, the TPB can be used in a setting of voluntary human behaviour to predict individual intention to perform a single behaviour (Fishbein and Ajzen, 1975). Individuals can voluntary decide to participate in online idea generation initiatives which makes the model of TPB applicable for this study. TPB states that to predict behavioral intention, the attitude and subjective norm towards the behaviour must be taken into account (Fishbein and Ajzen, 1975).
2.6.1 Perceived Behavioural Control - Self-efficacy
A possible short coming of the uses and gratification framework to predict intention to participate is it does not fully consider that other aspects such as self-efficacy may have an influence on the intention to participate in an activity. According to Ajzen (Ajzen, 1991; Ajzen and Driver, 1992; Ajzen and Madden, 1986), self-efficacy is the second component of perceived behavioral control (PBC). PBC is about the beliefs towards the access of resources needed to perform a behavior. In other words, PBC are the internal and external factors that may obstruct performance of the behavior. The first component consists of the availability of time, money or other specialized resources, these are the facilitating conditions (Triandis, 1979). Apart from time, these facilitating conditions are often accounted for by the host in the case of idea generation initiatives. The second component, self-efficacy, concerns an individual's self-confidence in his or her ability to perform a behavior (Bandura, 1982). For instance, an individual may feel that he or
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she does not have the capability to contribute to an idea generation initiative, in this case the intentions to participate will most likely decrease and the other way around.
H6: A higher perceived level of ‘self-efficacy’ will lead to a higher intention to participate in online idea generation co-creation initiatives.
2.6.2 Self-efficacy moderated by direct compensation
Compeau and Higgins (1991b) showed in their study that self-efficacy has a significant impact on usage and engagement. This impact might be moderated by an opportunity to gain a direct reward. For example, an extrinsically motivated individual may have high value for rewards. In turn the intention to participate will increase if the individual finds him or herself capable of doing the tasks proposed by an idea generation initiator as they believe that their chance of winning the reward/ gaining the prize will increase. On the other hand, when they do not believe they are capable of performing the task, intention to participate will decrease, however when they believe there are opportunities to get a ‘direct compensation’ they might go for it anyway to have a chance to win or gain a the reward.
This paper researches ‘direct compensation’ as a moderator of the effects of motivation, and of the interaction of different types of motivations, on intention to participate. This study proposes that that a part of the effect of intrinsic motivation is depends on the availability of rewards (Deci et al, 1999).
H7: The greater the level of ‘Direct compensation’, the lower the impact ‘Self –efficacy’ will have on intention to participate in online idea generation co-creation initiatives.
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2.6.3 Attitude
Attitude is the result of learning of a person based on a past experience. It represents the overall evaluation of an individual about a certain act or object (Eagly & Chaiken, 1993). Additionally, attitude is derived from the personal belief that intended behaviour will result in a certain outcome, and an evaluation by the individual if this outcome is desirable or not (Taylor and Todd, 1995). Prior research showed that attitude and motivation are closely related and highly interdependent (Peak, 1955). A basis for differences in action is the difference between attitudes of individuals. Ajzen (1975) describes attitude by means of three features: an individual learns an attitude, the attitude influences action and that action is in favor of behavioral intention.
2.6.3.1 Trust
In order for trust to exist, there must be uncertainty about a potential or existing relationship that leads to a perception of risk or vulnerability (McKnight, 2002). Trust can be defined as the willingness to rely on a third party taking into account integrity, ability and benevolence (Bhattacherje, 2002). Integrity concerns moral and ethical behaviour by the trustee that are acceptable for the trusting party. Ability refers to skills and competences of the trustee that are related to the trusting party. Benevolence are perceptions of goodwill of the trustee by the trusting party (Mayer, 1995). Positive believes by the trusting party about these three factors concerning the trustee might lead to a willingness of the trusting party to rely on the trustee in the expectation of a specific outcome (Koufaris, 2004).
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2.6.3.2 Attitude as mediator between trust and intention to participate
Overall, trust has a positive effect on customer attitude towards the company and customers who trust a company are more likely to use its service or product (Jarvenpaa, 2000). Applied to an online idea generation context, individuals might have a more positive attitude towards online idea generation initiatives if they have higher levels of trust in companies providing such initiatives. Leimeister, (2005) argues that trust in operators that initiate idea generation is an important aspect for participation and stems from technical components geared toward supporting incentives, activation, competence and benevolence. The Theory of reasoned action implies that attitude stems from initial beliefs about a subject (Ajzen, 1975). Trust can be seen as an initial believe and therefore may be a predictor of attitude. However this study also suggest an alternate path that is in contradiction with the TRA model. The TRA model argues that attitude completely mediates the relationship between beliefs and intention. Trust might have a significant impact on intention to participate regardless of an individual’s overall attitude. In other words, an individual might have an overall positive attitude regarding co-creation and idea generation, however still does not participate due to a lack of trust in companies providing co-creation possibilities. Therefore two hypotheses are proposed:
H8: A higher perceived level of ‘Trust’ will lead to a higher intention to participate in online idea generation co-creation initiatives.
H9: ‘Trust’ will have a positive direct relationship with attitude towards intention to participate in online idea generation initiatives.
H10: ‘Attitude’ will have a positive direct relationship with attitude towards intention to participate in online idea generation initiatives.
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2.6.4 Subjective norm
Subjective norm is the second factor of the TPB that has a direct influence on behavioural intention (Fishbein and Ajzen, 1975). Subjective norm can be described as the perceived social pressure an individual experiences from specific reference persons in performing the behaviour (Ajzen, 1975). Vankatesh and Davis (2000) add that an individual might choose a certain behaviour although they are not favorable towards their behaviour. This might occur when an individual is convinced that people important to him or her believe one should behave a certain way. In other words, subjective norm suggests that an individual’s believe of how others will view them when acting a certain way, will influence how they will behave. Therefore it can be argued that social pressures have an impact on motivation. Leimeister (2009) claims that the motivation to participate in for example a competition will be greater when significant others display the importance of participating. When applied in online idea generation initiatives, an individual might believe that people important to him or her favor participation in idea generation initiatives and therefore the individual might expect positive reactions when he or she actually participates.
H11: Subjective norm has a positive direct effect on intention to participate in online idea generation co-creation initiatives.
2.6.4.1 Community identification
An online community can be defined as a group of people who communicate with each other via the internet, have similar goals and ideas, without any geographical location nor ethnic origin constraints (Hsu, 2007). In turn, community identification involves a situation in which an individual perceives him or herself as being part of such a community (Nahaphiet and Ghosal,
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1998). Firms that engage in online idea generation often expose their initiative at online crowdsourcing communities, notable examples are Threadless, iStockphoto, eYeka, InnoCentive and the Goldcorp Challenge (Brabham, 2008). This study focuses on the online communities of eYeka and InnoCentive and the intention to participate in online idea generation initiatives of their members. A description of both communities will be given in chapter 4. Earlier research claims that the level of self-awareness of an individual impacts their sense of belonging to a particular community (Bergami, 2000; Dholakia, 2004). This research suggest that individuals that feel a strong connection to their community view other members of their community as important to them. In turn, an individual’s behaviour will be influenced by his or her believe of the opinions of other members of their community.
H12: The greater the level of ‘community identification’, the more impact ‘subjective norm’ will have on intention to participate in online idea generation co-creation initiatives.
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2.7 Main research question, hypotheses, and conceptual model
The aim of this study is to determine the main motivational drivers of individuals and their impact, predicting an individual’s intention to participate in online idea generation initiatives. The main research question is:
What are the main motivational drivers that stimulate individuals to voluntary participate in online idea generation initiatives, and to what extent do these drivers impact an individual’s intention to participate in
online idea generation initiatives?
Figure 2 presents the various motivational drivers derived from the literature combined into a conceptual
model. The hypotheses are:
H1: A greater perceived opportunity for ‘learning’ possibilities leads to a greater intention to participate in online idea generation co-creation initiatives.
H2: A greater perceived opportunity for ‘Social integrative’ possibilities leads to a greater intention to participate in online idea generation co-creation initiatives.
H3: A greater perceived opportunity for ‘Personal integrative’ possibilities leads to a greater intention to participate in online idea generation co-creation initiatives.
H4: A greater perceived opportunity for ‘Hedonic integrative’ possibilities leads to a greater intention to participate in online idea generation co-creation initiatives.
H5: A greater perceived opportunity for ‘Direct Compensation’ possibilities leads to a greater intention to participate in online idea generation co-creation initiatives.
H6: A higher perceived level of ‘Self-efficacy’ will lead to a higher intention to participate in online idea generation co-creation initiatives.
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H7: The greater the level of ‘Direct compensation’, the lower the impact ‘Self –efficacy’ will have on intention to participate in online idea generation co-creation initiatives.
H8: A higher perceived level of ‘Trust’ will lead to a higher intention to participate in online idea generation co-creation initiatives.
H9: ‘Trust’ will have a positive direct relationship with attitude towards intention to participate in online idea generation initiatives.
H10: ‘Attitude’ will have a positive direct relationship with attitude towards intention to participate in online idea generation initiatives.
H11: Subjective norm has a positive direct effect on intention to participate in online idea generation co-creation initiatives.
H12: The greater the level of ‘community identification’, the more impact ‘subjective norm’ will have on intention to participate in online idea generation co-creation initiatives.
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3. Methodology
The methodology section consists of the study’s research design, a description of the population sample and the process of data collection. Next, the measurement scales and survey outline are discussed. The chapter ends with a description of the statistical procedure used to process and analyse the obtained data.
3.1 Research design
The research will take a quantitative approach by collecting numerical primary data in order to test the proposed conceptual model. Quantitative research allows for the validation of proposed associations between variables, and in turn this allows for prediction of phenomena (Leedy and Ormrod, 2005). An online survey will confront respondents with a number of statements. Respondents are asked to indicate the degree to which they agree or disagree with each statement. In turn, each statement is related to a variable of the conceptual model and were derived from pre-defined scale instruments as pre-defined in literature from peer to peer reviewed academic journals. 3.2 Population, sample and data collection
The focal population of this study consisted of individuals that have participated in an online idea generation initiative at least once in order to collect accurate responses and generate reliable results. The survey was constructed by use of the software for web-based surveys by Qualtrics and was distributed in the English language. The study used a convenience sample and was partially based on self-selection. The survey was distributed via the forums of InnoCentive and eYeka and via Facebook. In order to do this the researcher created an online account for each forum and made contact with the population via this account, starting with a short post on the forum (appendix A). Self-selection took place by sharing survey invitations via posts on the forums and posts on various
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Facebook pages. Primary reasons for these distributions were large range, low costs and a relatively fast distribution. The link to the survey was online from until a sufficient amount of respondents was collected from the 1st of May until the 26th of May, hereafter the data collection was ended. 3.3 eYeka, InnoCentive, Facebook
As previously discussed, Facebook was one of the distribution channels used to send out the survey. The individuals that use Facebook have a high variety and therefore the ssurvey included the question if the respondent had ever participated in an online idea generation initiative. This in order to filter out those respondents that have never participated in such an initiative. In addition, a large number of co-creation platforms were contacted to be able to capture a significant amount of respondents that have participated in online idea generation initiatives. A few examples are: IdeaConnection, Threadless, PRESANS, Hypios, One Billion Minds, Ideaken, Idea Bounty, Battle of Concepts, crowdSPRING, 99designs, Treadless, eYeka and InnoCentive. For each platform an account was created in order to contact the moderators of the platform to ask for permission to approach send out the survey to their community members. For almost all platforms, except for eYeka and InnoCentive, permission was declined or members did not want to participate. However, for eYeka and InnoCentive permission was granted and community members were open to participate.
3.3.1 InnoCentive
InnoCentive is a co-creation platform who claim to crowdsource innovation solutions from the world’s smartest people, who compete to provide ideas and solutions to important business, social, policy, scientific, and technical challenges. Additionally, they argue that by unleashing human creativity, passion and diversity, problems can be solved that matter to business and society.
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Problems are solved better, faster, and at a lower cost than ever before, once one untether the search for solutions from an individual, department or company. They have a global network of millions of problem solvers, a proven challenge methodology and a cloud-based innovation management platform. Potential solvers are able to register for free at InnoCentive. They then only need to supply contact information, indicate areas of research interest. Furthermore, members do not need to be professional scientists, scholars or educated business people, anyone can get involved. Submitting a solution can often be done by simply the uploading a word-processed solution written into a downloadable template (Lakhani et al., 2007).
3.3.2 eYeka
Were InnoCentive focusses more on straightforward business challenges and solutions, eYeka is a platform that focuses more on creativity. They present the platform as follows: ‘eYeka is the world’s largest creative playground, a world of ideas for better brands’. eYeka has a broad variety of community members for more than 150 countries representing all continents. The platform claims to help their creative community to improve on its creative skills, work with the biggest global brands and their agencies, and get rewarded for creating high quality content and ideas. In addition, companies can upload their problem or challenge which will be distributed to all community members. In order to participate in eYeka co-creation challenges, individuals can register for free and fill out personal details and preferences, which is similar to InnoCentive. Anyone is allowed to create an account and submit solutions for any challenge they perceive to be interesting.
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3.4 Measures and survey outline
In this study eleven constructs are measured: ‘Intention to participate’, ‘Learning’, ‘Social integrative’, ‘Personal integrative’, ‘Hedonic integrative’, ‘Direct compensation’, ‘Self-efficacy’, ‘Trust’, ‘Attitude’, ‘Subjective norm’, ‘Community identity’. All constructs were measured by use of a five-point Likert scale to maintain instrument consistency. Respondents were asked to indicate their levels of agreement or disagreement with a given statement. The scale had a range from ‘strongly disagree’ to ‘strongly agree’. Previous studies showed that Likert scales are a reliable measure for human behaviour (Carter, 2009, Oliver, 1982). All measurement instruments were validated in prior literature.
3.4.1 Intention to participate
A four item scale was used to measure ‘intention to participate’. The items were adapted from Venkatesh et al. (2003) and Taylor, S., & Todd (1995). These items are (1) “I will try to participate in idea generation contests more frequently in the future”, (2) “I plan to participate more in idea generation contests in the future”, (3) “I intend to participate in idea generation contests more in the future” and (4) “I expect to participate in idea generation contests”.
3.4.2 Perceived benefits
The items of four of the constructs that measure perceived befits were adapted from Nambisan (2009). All items begin with the sentence: “I am more likely to participate in idea generation co-creation activities when such activities”, followed by an item in the form of a statement. A three item scale was used for ‘Learning’ and ‘Social integrative’. For ‘Learning’ these items are (1) “Enhance my knowledge about the product and its usage” (2) “Enhance my knowledge on product trends, related products and technology” and (3) “Help me make better
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product decisions as consumers”. For ‘Social integrative’ the items are (1) “Expand my personal network”, (2) “Enhance my sense of belongingness with this community.” and (3) “Enhance the strength of my affiliation with the customer community”. ‘Personal integrative’ and ‘Hedonic integrative’ were measured using a four item scale. For ‘Personal integrative’ the following items were used: (1) “Raise my status/reputation as product expert in my personal network”, (2) “Offer me satisfaction from influencing product design and development”, (3) “Offer me satisfaction from influencing product usage by other customers”, (4) “Offer me satisfaction from helping design better products”. In turn, for ‘Hedonic integrative’ the next to mention items were used (1) “Contribute in spending some enjoyable and relaxing time”, (2) “Contribute in fun and pleasure”, (3) “Entertain and stimulate my mind” and (4) “Offer me enjoyment deriving from problem solving, idea generation”. The fifth construct measuring perceived benefit, ‘Direct compensation’, had a six item scale and was adapted from Leimeister (2009), Hars and Ou (2001) and Richins (1992). The items used were (1) “Enhance my financial position directly”, (2) “Contribute in creating cheaper products”, (3) “Enhance my financial position indirectly”, (4) “Deliver non-financial rewards”, (5) “Offer me the opportunity to win a monetary or nonmonetary prize” and (6) “Offer me the chance to work for the company”.
3.4.3 Self-efficacy
The construct ‘Self-efficacy’ was measured by the two item scale by Hsu et al. (2007). The items used were (1) “I am competent to participate in idea generation co-creation initiatives” and “I have the expertise needed to engage in idea generation co-creation initiatives”.
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3.4.4 Trust
‘Trust’ was measured by a four item scale adapted from Valacich (2006) and Garbarino (1999). Items used were (1) “Most companies engaged in co-creation idea generation are concerned about their participants”, (2) “Organizational intentions cannot be trusted at times” (reversed coded), (3) “Idea generation facilitators would be honest with in their dealings with the community” and (4) “Idea generation facilitators truthfully provide information on contest tasks”. 3.4.5 Attitude
The variable ‘Attitude’ was measured by a four item scale by Taylor and Todd (1995) which measures attitudes and perceptions of individuals. Items used were (1) “Participation in idea generation creation is a good idea”, (2) “I like the idea of participation in idea generation co-creation”, (3) “Participation in idea generation co-creation is a pleasant experience” and (4) “Participation in idea generation co-creation is a foolish idea” (reverse coded).
3.4.6 Subjective norm
For ‘Subjective norm’ a four item scale was used derived from Venkatesh et al. (2003) and Hsu et al. (2008). Items used were (1) “Most people whose opinion I value think that participating in idea generation contests is important”, (2) “Most people value participation in idea generation contests as an important issue”, (3) “People important to me encourage my participation in idea generation contests” and (4) “People important to me think I should participate in idea generation contests”.
3.4.7 Community Identification
The eleventh item ‘Community identification’ was measured using a four item scale designed by Chiu et al. (2006). The following items were used (1) “Participating in idea generation
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co-creation will give me a sense of belonging in my community”, (2) “I feel a strong bond to fellow members of my community”, (3) “I am likely to have a strong positive feeling towards idea generation co-creation in my community” and (4) “I am a proud member of my community”. 3.4.8 Demographic variables
Additionally, this study records respondents’ demographics in the form of gender, age, education level and current occupation. Gender was measured by means of a two option multiple choice option: male or female. Next, respondents were asked to indicate into which category their age falls, starting from age lower than 18 as minimum and age greater than 50 as maximum. Educational level was measured by a five item multiple choice question ranging from primary school certificate to university degree. Last, respondents filled out there current occupation by means of a four item multiple choice question, indicating if the respondent was formally employed, self-employed, unemployed or in school.
3.5 Survey outline
The survey started with an informative statement containing the purpose of the research and confirming that there are no right or wrong answers. Moreover the statement indicated that the results were anonymous and treated confidentially. The following item of the survey provides a short introduction and explanation about the concept of co-creation and online idea generation initiatives. Next, each respondent was asked if he or she had ever participated in an online idea generation initiative in order to be able filter out the respondents who did not. Thereafter, respondents were asked to indicate to which degree they agree or disagree with statements regarding the variables of the conceptual model. Finally, the respondents were thanked for their
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participation and the researchers contact details were provide in case of any questions or remarks by the respondents. The full survey can be found in appendix B.
3.6 Statistical procedure
The Statistical software Package for Social Sciences (SPSS) was used to perform all statistical procedures. A 95% confidence interval was used for all statistical tests. The following analytical strategy was used to process the data. First, frequency checks for each item were done and missing values were identified. Due to a large sample size excluding missing values listwise was applicable throughout the analysis. Additionally, cross-tabulations were done between the controlling variables. Next, scale reliability was checked for all constructs by use of Cronbach’s alpha. Thereafter, descriptive statistics, normality and a correlation analysis was done for all variables. Finally, the hypotheses were tested based on the results of the preliminary checks.
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4. Results and Analysis
In this chapter the results of the data analysis will be presented. The chapter starts with a discussion of the sample characteristics followed by a description of the approach used for data screening and preliminary checks. Thereafter, an analysis of the results of hypothesis testing are presented.
4.1 Sample characteristics
It is unknown how many individuals were exposed to the generic questionnaire that was distributed on the forum of Innocentive, on the forum of eYeka and via Facebook. Of the 311 recorded responses a total of 225 survey responses were usable for analysis (completion rate of 72%). The other 86 responses excluded from analysis due to incompletion of the survey or due to respondents that answered ‘no’ on the question if they have ever participated in an idea generation co-creation initiative. The responses were collected over 4 weeks starting from the 1st of May until the 26st of May 2015.
Table 1 shows the gender distribution of the respondents. It indicates that of the 225 respondents the female respondents were slightly over-represented with 55.1% compared to 44.9% male respondents.
Gender Profile
Frequency Percent Valid Percent Cumulative
Percent
Valid Male 101 44,9 44,9 44,9
Female 124 55,1 55,1 100
Total 225 100 100
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An overview of the age distribution of the respondents is displayed in table 2. The majority of respondents were aged between 21 and 35 with a representation of 85.8 %. Next, respondents with an age below 20 represented 7.1%. This was followed by respondents aged between 36 and 50 representing 4.4% and respondents over and age of 50 representing 2.7%.
Age profile
Frequency Percent Valid Percent Cumulative
Percent Valid < 20 16 7,1 7,1 7,1 21 - 35 193 85,8 85,8 92,9 36 - 50 10 4,4 4,4 97,3 > 50 6 2,7 2,7 100 Total 225 100 100
Table 2 Age profile
Additionally, the highest education level obtained by the respondents was measured. Table 3 indicates that the majority of the respondents that have participated in idea generation initiatives have enjoyed a relatively high education. 28% obtained a diploma at a Higher Professional education and 58.7% obtained a University degree. This was followed by professional education, secondary school certificate and primary school certificate with 7.1%, 5.3% and 0.9% respectively.
Highest education level obtained
Level Frequency Percent Valid Percent Cumulative
Percent
Valid Primary school certificate 2 0,9 0,9 0,9
Secondary school certificate 12 5,3 5,3 6,2
Professional education 16 7,1 7,1 13,3
Higher Professional Education 63 28 28 41,3
University Degree 132 58,7 58,7 100
Total 225 100 100
Table 3 Highest education level obtained
In table 4 an overview of the respondents current occupation can be found. A small majority, 52.4%, of the respondents is found to be still in school. Followed by 41.3% of the
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respondents that indicated to be employed, either self-employed (8%) or formally employed (33.3%). The last 6.2% of the respondents is currently unemployed.
Current occupation of respondents
Frequency Percent Valid Percent Cumulative Percent Valid Self-Employed 18 8 8 8 Formally employed 75 33,3 33,3 41,3 Currently unemployed 14 6,2 6,2 47,6 Currently in school 118 52,4 52,4 100 Total 225 100 100
Table 4 Current occupation of respondents
4.2 Cross-tabulations
Cross-tabulations were done on ‘Age’, ‘Gender’, ‘Highest education level’ and ‘Current occupation’ in order to establish demographic patterns and to generate a clear overview of the sample population.
4.2.1 Gender - Highest education level
Table 5 displays that of the majority of respondents with a University degree, 79 (60%) are female and 53 (40%) are male. Additionally, respondents in Higher Professional education, 37 (58.7%) are female and 26 (41.3%) are male. For respondents that obtained a Professional education, 12 (75%) were male and 4 (25%) were female. Similarly, for secondary school certificate, 9 (75%) of the respondents were male and 3 (25%) were female.
