UNIVERSITEIT GENT GHENT UNIVERSITY

FACULTEIT ECONOMIE EN BEDRIJFSKUNDE FACULTY OF ECONOMICS AND BUSINESS ADMINISTRATION ACADEMIC YEAR 2015-2016

Grassroots innovation in Flanders

Masterproef voorgedragen tot het bekomen van de graad van Master’s Dissertation submitted to obtain the degree of Master of Science in de Toegepaste Economische Wetenschappen: Handelsingenieur Master of Science in Business Engineering Merijn Debacker

onder leiding van under the guidance of

Prof. Isabel Verniers

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UNIVERSITEIT GENT GHENT UNIVERSITY

FACULTEIT ECONOMIE EN BEDRIJFSKUNDE FACULTY OF ECONOMICS AND BUSINESS ADMINISTRATION ACADEMIC YEAR 2015-2016

Grassroots innovation in Flanders

Masterproef voorgedragen tot het bekomen van de graad van Master’s Dissertation submitted to obtain the degree of Master of Science in de Toegepaste Economische Wetenschappen: Handelsingenieur Master of Science in Business Engineering Merijn Debacker

onder leiding van under the guidance of

Prof. Isabel Verniers

iii

CONFIDENTIALITY CLAUSE PERMISSION Ondergetekende verklaart dat de inhoud van deze masterproef mag geraadpleegd en/of gereproduceerd worden, mits bronvermelding. Merijn Debacker

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DUTCH SUMMARY Deze masterproef bestaat uit drie grote delen. Eerst bespreek ik de literatuur rond innovatie en werknemersgedreven innovatie, daarna mijn onderzoek, om te eindigen met een conclusie, beperkingen en aanbevelingen voor verder onderzoek.

Het eerste hoofdstuk start met een introductie tot innovatie, waarbij een onderscheid wordt gemaakt tussen soorten innovatie. Daarna worden de voor- en nadelen in relatie tot innovatie van grote bedrijven ten opzichte van kleine bedrijven besproken. Het tweede hoofdstuk behandelt het belang van innovatie voor zoveel overheden als bedrijven, als motivatie voor dit onderzoek. In het derde hoofdstuk behandel ik kort innovatie in Vlaanderen, aan de hand van tabellen en cijfers. Daarna bespreek ik de literatuur rond ‘the wisdom of crowds’, waarbij bewezen is dat een massa creatiever en intelligenter kan zijn dan experts. In hoofdstuk vijf bespreek ik werknemersgedreven innovatie, het belang en de voordelen hiervan. Hierbij bespreek ik ook twee case studies, GameChanger en Innospire. In hoofdstuk zes bespreek ik nog specifieke literatuur en maak zo hypothesen op om correlaties te meten tussen werknemersgedreven innovatie aan de ene kant en demografische eigenschappen van het bedrijf en de werknemers, intrinsieke motivatie, bedrijfscultuur, centralisatie en formalisatie aan de andere kant.

Het tweede onderdeel van deze masterproef behandelt het onderzoek zelf. Eerst wordt de werkwijze van het onderzoek besproken, daarna de demografie van de respondenten en een beschrijving van hun antwoorden. Hierna analyseer ik de resultaten om deze te toetsen aan mijn hypotheses. Hier blijken significante correlaties te bestaan tussen werknemersgedreven innovatie aan de ene kant en opleidingsniveau van de werknemer, intrinsieke motivatie, bedrijfscultuur, centralisatie (-) en formalisatie (-) aan de andere kant.

Het laatste onderdeel vat deze masterproef samen, geeft de beperkingen van het onderzoek weer en aanbevelingen voor verder onderzoek. De grootste beperking is waarschijnlijk het aantal respondenten (105 bruikbare enquêtes) en de oververtegenwoordiging van jonge mensen als respondent.

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FOREWORD I would like to thank my promotor, Isabel Verniers, for her valuable information, guidelines, shared knowledge and recommendations.

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TABLE OF CONTENTS PART 1: LITERATURE REVIEW .......................................................... 1 1. Introduction ..................................................................................................................................... 1 1.1 Definitions of innovation ........................................................................................................... 1 1.2 Corporations versus start-ups on radical innovations ................................................................ 2 2. Importance of innovation ................................................................................................................ 3 2.1 Importance for the economy ...................................................................................................... 3 2.2 Importance for companies ......................................................................................................... 4 3. Innovation in Flanders ..................................................................................................................... 4 4. The wisdom of crowds .................................................................................................................... 6 5. Grassroots innovation ...................................................................................................................... 7 5.1 Incremental grassroots innovation ............................................................................................. 9 5.2 Radical grassroots innovation: GameChanger and Innospire.................................................. 10 5.3 Other radical grassroots innovation programs ......................................................................... 13 6. Hypotheses .................................................................................................................................... 16 6.1 Dependent variables ................................................................................................................ 16 6.2 Independent variables .............................................................................................................. 16 6.3 Summary ................................................................................................................................. 22

PART 2: RESEARCH .............................................................................. 24 7. Methodology ................................................................................................................................. 24 7.1 Pretesting ................................................................................................................................. 24 7.2 Survey...................................................................................................................................... 24 8. Analyses, results and conclusion ................................................................................................... 28 8.1 Hypotheses 1 and 2: firm size, technology level and HR ........................................................ 28 8.2 Hypothesis 3 : Self-determination theory ................................................................................ 29 8.3 Hypotheses 4 and 5: Company culture .................................................................................... 29 8.4 Hypothesis 6a and 6b: Centralization and formalization......................................................... 31 8.5 Regression ............................................................................................................................... 32

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PART 3: CONCLUSION, LIMITATIONS AND RECOMMENDATIONS ......................................................................... 34 9. Conclusion ..................................................................................................................................... 34 10. Limitations................................................................................................................................... 35 11. Recommendations ....................................................................................................................... 35

BIBLIOGRAPHY ..................................................................................... 36 APPENDIX ................................................................................................ 42 Appendix 1: Questionnaire ................................................................................................................ 42 Appendix 2: SPSS output .................................................................................................................. 49

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LIST OF TABLES Table 6.1: Hypotheses .............................................................................................................. 23 Table 7.1: Demographics of respondents ................................................................................. 26 Table 7.2: Descriptive of scales ............................................................................................... 27 Table 8.1: Summary of the research ......................................................................................... 32 Table 8.2: Regression…………………………………………………………………………33

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LIST OF FIGURES Figure 2.1: Correlation of GDP/capita and the global innovation index.................................... 4 Figure 4.1: Evolution of R&D spending in Flanders ................................................................. 5 Figure 4.2: Internation comparison of R&D spending ............................................................... 5 Figure 5.1: Innovation accountability ........................................................................................ 8 Figure 5.2: Motivation of Merck employees ............................................................................ 12 Figure 6.1: Self determination theory....................................................................................... 18 Figure 6.2: CEAI ...................................................................................................................... 21 Figure 7.1: Grassroots maturity ................................................................................................ 27 Figure 7.2: Innovation motivation ............................................................................................ 27 Figure 7.3: Incremental and radical innovation ....................................................................... 27

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LIST OF ABBREVIATIONS CEAI= Corporate Entrepreneurship Assessment Instrument CENTR= centralization CET= Cognitive evaluation theory Cf. = confer, see EO= Entrepreneurial Orientation FORM= formalization GERD= gross domestic expenditure on R&D R&D= Research & Development SDT= Self-determination theory

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ABSTRACT I have questioned 105 employees on their innovation motivation and actual input of ideas for both radical and incremental innovations. Summing up these three factors, I constructed the ‘grassroots innovation involvement’ variable. Five factors were correlated with grassroots innovation involvement, namely education, intrinsic motivation, CEAI, formalization (-) and centralization (-). Entrepreneurial Orientation, firm size and sector were not found to be correlated

to

grassroots

innovation

involvement

in

this

research.

Interestingly,

‘connectedness’, a sub construct of intrinsic motivation seems to have a very strong correlation to grassroots innovation involvement, whilst ‘rewards’, a sub construct of CEAI does not seem to be correlated with grassroots innovation involvement.

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PART 1: LITERATURE REVIEW

1. Introduction 1.1 Definitions of innovation

‘Ideas come from people. Innovation is a capability of the many.’ Dr. Steven Brandt - Stanford University

Innovation is defined by the Organization for Economic Co-operation and Development as ‘the implementation of a new or significantly improved product (good or service) or process, a new marketing method, or a new organizational method in business practices, workplace organization or external relations’ (Oslo Manual, 2005, p. 46). Innovation can be viewed as a better solution to existing or to unexpressed market needs (Maryville, 1992).

I will subdivide innovation in radical versus incremental and bottom-up versus top-down innovation. Incremental innovation focuses on cost or feature improvements in existing products, services, processes, marketing or business models. It allows for competitiveness with current markets and has a rather low uncertainty or risk. Incremental innovations do not involve substantial changes in technical skills, knowledge or design. Most innovation efforts result in incremental innovations (Griffin, 1997). For example, the number of transistors in a dense electrical circuit doubles approximately every two years (Moore, 1975). This enables higher computing capabilities for electronic devices. Another example is the automobile industry, where incremental changes have increased speed, safety, luxury etc. over the years.

Radical innovation, on the other hand, focuses on processes, products or services with unprecedented performance features. It creates a dramatic change that transforms the existing market or industries, or creates new ones. A radical innovation is one ‘that sweeps away much of a firm's existing investment in technical skills and knowledge, designs, production technique, plant, and equipment’ (Utterback, 1994). This innovation explores new technology, but it is more uncertain and bears a high risk. For example, the first low priced car, the Ford Model T changed the transport industry by shifting from horse drawn vehicles to motorized vehicles. Firms introducing more advanced innovations are relying to a higher extent on R&D

and patents and cooperate more often with universities and research organizations. Firms introducing less advanced innovations rely more on knowledge links with business services (Tödtling, Lehner, & Kaufmann, 2008).

The second subdivision is between top-down and bottom-up innovation. Top-down innovation is an innovation culture with a strong hierarchy where employees must work on ideas selected by management. Management sets the targets and the objectives and provides the funding. The implementation is left to the appropriate personnel. Bottom-up or grassroots innovation is ‘a process where the employee crowd comes up with innovative ideas and develops them into marketed products, making innovation everyone’s responsibility’ (Stremersch, 2015). Employees are invited to bring up and work out their ideas to improve the company. Grassroots innovation relates to the concepts of non-R&D innovation, non-technological innovation and high-involvement innovation and tends to be overlooked in research (Høyrup, 2010).

1.2 Corporations versus start-ups on radical innovations Big corporations have a couple of advantages over entrepreneurs: they have an established customer base and established distribution channels, more financial capabilities, and economies of scope to spread the risks of new ventures (Arrow, 1962). Their financial capabilities enable them to hire high quality scientific personnel and to maintain scientific facilities (Chandy & Tellis, 2000). However, small firms spend their R&D budget more efficient (Griliches, 1990; Scherer, 1983) and they have significantly shorter development times (Griffin, 2002). It appears to be difficult for incumbent firms to dynamically renew existing capabilities (Tushman & Anderson, 1986; Tripsas, 1997), because they face some common pitfalls that inhibit radical innovation (Assink, 2006).

First, companies can be unwilling to cannibalize their own investments and assets (Chandy & Tellis, 1998). Second, dominant design causes companies to focus too long on incremental innovations on successful concepts from the past. Third, disruptive innovations carry high risk, uncertainty, and unpredictability. This makes it hard to obtain long-term internal support and resources (Sandberg, 2002). A lot of companies have a risk-averse climate. Fourth, innovation process mismanagement is the biggest inhibitor of growth for large companies (Stringer, 2000). Innovation is a process consisting of two stages: initiation and 2

implementation. In the initiation stage, people explore opportunities and gather ideas. In the implementation stage, people develop, test and commercialize a promising idea (Zaltman, Duncan, & Holbek 1973). Not idea generation, but idea development and marketing are the bottleneck in most companies. Innovation is just not working out the way most companies want and expect (Koetzier & Alon, 2013). Two successful case studies (chapter 6.2) will report on an efficient and effective radical grassroots innovation process.

Large companies thus have a problem with radical innovation: whilst it is very important (cf. infra), few companies are successful with developing it. However, there is a vast opportunity for large companies: they have advantages that cannot be copied by start-ups, while they can work away their disadvantages by copying startup behavior. A possible solution for companies struggling with innovation could be an ambidextrous approach (Daft, 1978). An ambidextrous organization combines consistency for incremental innovation with flexibility and experimenting capabilities for radical innovations.

2. Importance of innovation 2.1 Importance for the economy Solow and other economists found that 85% of actual growth in the output of the economy in highly industrialized countries is due to technological innovation (Rosenberg, 2004). ‘The research to date strongly suggests that technical progress, the embodiment of innovation, is the fundamental determinant of longer-term productivity performance, hence international competitiveness, living standards and quality of life’ (Rao, Ahmad, Horsman, & KapteinRussell, 2001). Innovative activity is highly positively related to productivity and per-capita income in both developed and developing countries (figure 2.1). Breakthroughs in medicine and technology have significantly improved living standards around the world. Innovation is one of the main factors underlying countries’ international competitiveness as well as their productivity and output (Asheim & Isaksen, 1997; Michie, 1998). These results, that indicate a clear relationship between innovation and economic growth, caused the creation of a growing economic theory: innovation economics. This theory states that the central goal of economic policy should be to achieve higher productivity through greater innovation. This model places knowledge, technology, entrepreneurship, and innovation at the center of economic growth (Karlsson, Johansson, & Stough, 2013). 3

Figure 1.1: Correlation of GDP/capita and the global innovation index Source: http://stats.areppim.com/stats/stats_innovxgdp_correl_2011.htm

2.2 Importance for companies Globalization and outsourcing increase competition and push organizations to improve their efficiency and effectiveness. Post-industrial organizations are knowledge-based and their survival and success depend on creativity, innovation, discovery and inventiveness (Martens & Terblanche, 2003). Different studies have proven the importance of innovation for companies: ‘Innovation is a key factor for a company to survive and grow on the long run’ (Tidd, 2001). ‘The most important business issue of our time is finding a way to build companies where innovation is both radical and systemic’ (Hamel, 2002).

3. Innovation in Flanders The Flemish government is well aware of the importance of research and innovation as a necessary condition for maintaining wealth and well-being (Geerts, Van Langenhove, Viaene, & Dengis, 2013). Since 1995, it started to elaborate a broad-based strategy for the Science, Technology and Innovation policy. Flanders has the ambition to be among the top-5 innovative EU regions by 2020, by accomplishing three goals. First, Flemish public and private stakeholders committed themselves to invest more in R&D. The total Gross domestic expenditure on R&D (GERD) exceeded 5 billion euro in 2012 (figure 3.1). One can see that this is more than twice the spending in 1997. Second, Flanders will focus on 6 innovation hubs, like eco-innovation and sustainable energy, to implement a long-term vision for the future. Third, Flanders wants to create more opportunities for research talent by popularizing science, technology and innovation to young people. Figure 3.2 depicts Flemish GERD is

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now above the EU-28 average and Belgium’s average, but still lower than the USA, Germany and other top-innovative countries (Geerts et al., 2013).

Figure 2.1: Evolution of R&D spending in Flanders Source: STI in Flanders 2013

Figure 3.2: Internation comparison of R&D spending Source: STI in Flanders 2013

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4. The wisdom of crowds Francis Galton is much cited to be the first person to have observed ‘the wisdom of crowds’. Galton described his visit to a livestock fair where judges were invited to guess an ox’s weight after it was slaughtered and dressed (Galton, 1907). Nobody hit the mark, 1198 pounds, but Galton found that both the median (1207 pounds) and the mean (1197 pounds) of the guesses were more accurate than the estimates of most crowd members and more accurate than any of the individual estimates made by cattle experts.

The advantages of crowds over experts are twofold: first, crowds, if they are managed well, have more creativity. Second, ‘the collective intelligence of a large group of people beats the intelligence of any of the group members, even the experts’ (Stremersch, 2015; Galton, 1907).

It is indeed easy to understand that more people means more creativity. It is hard for a person to approach multiple ways to solving a problem (Larrick, Mannes, Soll, & Krueger, 2011), but different people have different perspectives and solutions to problems. Groups are better than individuals in creating a wider range of creative ideas, objectives, and alternatives (Larrick et al., 2011). For a certain problem, crowdsourcing process generated user ideas score significantly higher in terms of novelty and customer benefit in comparison with expert generated ideas (Poetz & Schreier, 2012). Second, the average prediction of a crowd always outperforms the crowd’s average member and with some regularity, all or almost all of their members (Page, 2007). Crowds with more diversity are wiser. In order to solve problems, a team of randomly selected intelligent agents outperforms a team comprised of the best-performing agents (Hong & Page, 2004). The reason is that the best-performing people are a homogenous group and they often have similar perspectives and use similar problem-solving techniques. A diverse crowd on the other hand will offer a multitude of perspectives. The best performing group’s relative greater ability is more than offset by their lack of problem-solving diversity. This is known as the ‘diversity trumps ability theorem’ (Hong et al., 2004). This implies that one’s ability to improve the collective decision determines one’s value in a team (Page & Hong, 2001). This is probably the reason why cross functional teams are the best source for new ideas (Cronin & Weingart, 2007). 6

A crowd can achieve better results when the experts (those who contribute most to the crowd’s performance) are identified and their opinions are aggregated, while ignoring the estimates of non-experts. This can be seen as a comprise between the power of the crowd and the expert approach (Budescu & Chen, 2014). It is thus optimal to make a group of smart people with different backgrounds and knowledge. Group intelligence is not strongly correlated with the average or maximum individual intelligence of group members. Just having a bunch of smart people in a group doesn’t necessarily make a smart group. Group intelligence, however, is strongly correlated with the members’ ability to reason about the mental states of others, what they feel, know and believe (Woolley et al., 2010). It is about the members’ ability to cooperate with each other. These abilities are not only important in offline, but also in online groups, which have extremely limited communication channels (Engel et al., 2014). However, the Innospire case study will show that crowds can be biased. ’Diversity’ in this theorem refers to a group of individuals with diverse problem representations of a problem and diverse algorithms to find a solution. Diversity can be produced by differences in identity (Nisbett, 2003) and different sources of experience and information, like education (Stinchcombe, 1990). A diverse team, with highly intelligent and conscientious individuals, who are interested in working in teams will provide the best results. In theory, groups of diverse, knowledgeable individuals should have more creativity and better solutions to problems than experts.

5. Grassroots innovation Grassroots innovation is ‘a process where the employee crowd comes up with innovative ideas and develops them into marketed products, making innovation everyone’s responsibility’. (Stremersh, 2015). The basic idea of grassroots innovation rests on the thought that employees have hidden abilities for innovation (Forssén, 2001), and that this can be used to ameliorate the company and its employees’ wellbeing (Kesting & Ulhoi, 2010). The idea also rests on a crowds’ wisdom and creativity (cf. chapter 5: The employee crowd). ‘In order to be sustainable, grassroots innovation processes need to combine bottom-up passion and engagement with a structured process that guarantees internal sponsorship and alignment with the company’s overall strategy.’ (Betz, Camacho, Gerards & Stremersch, 2013; Birkinshaw, Bouquet, & Barsoux, 2011). Grassroots innovation is increasingly seen as the most natural 7

and sustainable source of change (Huy & Mintzberg, 2003). In fact, grassroots innovations can be used in any sector because ‘creative ideas may be generated by employees in any job and at any level of the organization’ (Shalley & Gilson, 2004), if there is a foundation for organizational creativity and innovation (Amabile, 1997). 3M corporation was probably the first corporation that allowed grass-roots innovation. It has been allowing its scientists, ever since 1948, to spend up to 15% of their time in projects of their own interest.

Grassroots innovation requires a wrenching culture change within the company (Robinson & Schroeder, 2009). First, managers have to learn to accept that their subordinates can think out smarter ideas. Second, it is important that the company culture accepts failure. If people are afraid to ask questions or post ideas because they make them look bad, they will not try new things. Third, it is important to guarantee follow-up, support and implementation of good ideas. The suggestion-box, where employees can post ideas in a black box, can paradoxically be seen as a bottom-up innovation inhibitor. In the majority of companies where a suggestion box is used, nobody is held accountable for the generated ideas, which leads to long backlogs and makes the process ineffective (Fairbank, Spangler, & Williams, 2003). Accountability is very important in the innovation process: more successful innovative companies tend to have an executive accountable for innovation, as depicted in figure 5.1 (Miller, Klokgieters, Brankovic, & Duppen, 2012).

Figure 5.1: Innovation accountability Source: Miller, Klokgieters, Brankovic, & Duppen, 2012

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Some companies provide software to post, adjust and toss around ideas from employees on the corporate Intranet. Yambla, for example, is a Belgian start-up that offers a website and mobile application which allows employees to share their ideas in a short, descriptive message. This idea is then tossed around within the company, and Yambla measures the amount of support it gets and pushes promising ideas to the right people. Some companies provide more or less the same services: Innosect, PIT (acquired by KPMG), HYPE innovation, SpigitEngage, IdeaScale and Brightidea. Using this software can be seen as a rather non-invasive grassroots innovation, as the follow-up and accountability of these ideas are still not certain. Roughly, one can divide more formalized bottom-up innovation into two sections: incremental and radical innovations.

5.1 Incremental grassroots innovation With incremental bottom-up innovation, employees are invited to give improvement ideas. It is easy to see these incremental innovation as marginal, but over a certain time these are a significant factor in the strategic development of firms (Bessant & Tidd, 2009). Incremental bottom-up innovation was one of the keys to success of Toyota Production Systems and their Kaizen mentality (Nemoto, 1987). Their focus on front-line ideas became a distinguishing characteristic of Japanese management (Imai, 1986). These successful initiatives were picked up by other companies. I will only handle formalized grassroots innovation projects, because informal projects, like UBS resilience, tend to be only modestly successful. They may lack key benefits associated with top-down innovation, such as a direct alignment with the company’s goals and internal sponsorship (Birkinshaw et al., 2011). An example of incremental grassroots innovation is Starbucks (Gulati, Huffman, & Neilson, 2002), where employees have the autonomy to think about improvements for the brand. Quarterly, employees can share ideas, from which one is developed by R&D headquarters and offered to all the Starbucks markets. For example, one idea was to hold a Blended Beverage Rally, where employees learned in a fun way about the summer season’s offerings. Afterwards, they were given tangible incentives to sell the product, which drove sales notably. District managers can also be temporary project managers at Starbucks headquarters, because they provide valuable insight from the field. Feedback from employees is very important in new product development, because they know what new drinks the customer want.

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5.2 Radical grassroots innovation: GameChanger and Innospire Corporations can also perform a more radical bottom-up innovation. Employees can state their ideas, and when they are accepted, assemble a team and develop this idea into a business opportunity for the company. I will work with 2 case studies to further elaborate this procedure. These intrapreneurs do not have the opportunities to become very rich, but they have a better shot at success and far less financial and personal risk than entrepreneurs.

The first case study is about the Innospire process at Merck KGaA (Betz, Camacho, Gerards, & Stremersch, 2014). Merck is a global pharmaceutical and chemical company with € 10.3 billion in revenue in 2011 and employs 40.000 people in 67 countries. Their process, Innospire, has recently won the ‘Innovationspreis der deutschen Wirtschaft’ (the Innovation Award of the German economy), which is the world’s oldest innovation price. Academics consider innovation and therapy creation a very important area for life sciences firms (Stremersch, 2008). Improving R&D efficiency is the key challenge faced by pharmaceutical companies (Paul et al. 2010). Innospire, Merck’s formalized grassroots innovation initiative, is one of the first examples of grassroots innovation in life sciences. At the end of 2008, Innospire started as a project to collect and advance innovative ideas to generate new businesses at all levels in the company. The goals of Innospire were to mobilize the full innovation potential of their large organization, to promote networking across chemicals and pharmaceuticals divisions in order to boost cross-fertilization, to generate an innovation-friendly environment and to signal that innovation is important, even in financially unstable times. The entire Innospire process was managed and supervised by a dedicated team. This team branded and communicated this process in diverse ways. Top management was closely involved, the executives themselves sent a mail to all employees encouraging them to participate and to think outside-the-box. From the beginning, it was made clear this was not a pure idea contest, but that the idea owner would step into a process that would last for at least a year, where he or she can cooperate with a self-assembled team. There were few restrictions from the beginning and crossdivisional synergies between the chemical and pharmaceutical business were especially promoted. It was important to note that the time invested in the process is on top of the employees current duties. For one, it was almost impossible to take people from their current

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duties, and by stating this, only intrinsically motivated employees (cf. infra) would apply. In total 462 ideas from 32 countries were submitted from all divisions of Merck. In the first idea selection, an interdivisional committee of 17 people with diverse backgrounds, ranging from R&D, manufacturing, marketing, legal, IP, business development and HR, selected 17 ideas. This committee was not too critical, in order to signal that the company allows for failure and knowing that uninteresting projects would not be able to attract employees in the next step. This second reason follows the principle of ‘resource attraction’ (Hamel, 1998), where a company mimics the essential elements of the Silicon Valley ecosystem in order to enhance their innovation output. If an idea has merit in Silicon Valley, it will attract resources in the form of venture capital and talent, and there is no reason resource attraction can’t be made to work inside huge corporations (Hamel, 1998). In 2010, the second edition, the company chose the top 15 ideas that were not picked in the first edition, because a lot of good ideas were left in the idea pool in 2009. The 17 ‘intrapreneurs’ were now free to assemble a team in order to develop their promising ideas. There were two ways Merck facilitated the formation of teams. First, they organized innovation marketplaces at three major sites in order to foster team formation. Idea owners could present their ideas, discuss them with colleagues and recruit additional team members. Top management was present at all these events to signal their support. Second, idea owners could also put their videotaped oral presentation and a presentation file on the corporate Intranet. Here it was clearly stated what expertise and knowledge the team was still looking for. Most idea owners were scientists and they searched experienced business developers, marketers and financial executives. A couple of months after the teams’ formation, there was a second selection round, where the 6 most promising teams were selected. In the first edition, the projects were selected by a jury on their progression, completeness of skill, business potential, probability of success and fit with Merck’s strategy. In the second edition, the company let the company’s employees discuss and vote for the different business projects. This created a strong engagement and the voting employees even contributed to further improvement. However, voters tended to choose projects of people they knew or for projects that had an emotional appeal (like new technology or ‘save the planet’ type). The finalists followed a 7 day bootcamp, where some followed basic management training, in order to optimize the business plan. This program assisted them in advancing their idea to a professional business plan. In the development, teams got help from a scientific advisory board and the patent and legal department. A grand jury, where all major divisions were 11

presented, hoping not to miss business opportunities, decided on the funding and further development of these business plans. In 2009, two projects received full Innospire funding, while three others were further developed within their respective divisions. These projects could now grow further independently of organizational constraints, for a certain timeframe. Teams had to report quarterly on their proceedings and the Innovation Steering Committee was responsible for approving budgets for the following years. The final customers of these Innospire projects were the respective strategic business units so it was crucial that the they were involved early on. It was important to adequately prepare and implement the transfer of projects from the team to this division, which requires extensive communication. The external consultants note that the real process really just starts after the grand jury approval. The incubation step is crucial to make the Innospire process sustainable.

Merck’s senior management is very enthusiastic about Innospire. The process has generated more than 20 patents and new business ideas that represent an estimated business volume between 200-500 million euro.1 In 2011 and 2013, there was a new call for Innospire ideas. The number of submitted ideas was up 20%, indicating the growth of interest of employees. Since 2013, Innospire has been open to external partners. People from outside the organization can post their ideas and, if promising, they are further developed within the company.

Merck

management

motivated their employees through 5 ways (figure 5.2). First, they gave employees enough

resources

(time,

personnel and budget) to work

on

their

project.

Second, senior management was visibly involved in the Innospire

process.

intrapreneurs financial also

were

incentives,

Third, given but

non-financial

Figure 5.2 Motivation of Merck employees Source: Betz, Camacho, Gerards, & Stremersch, 2014

incentives, like career rewards. Fourth, administrative and organizational structures were 12

deployed in order to support Innospire. Fifth, management promoted experimentation and smart risk taking by allowing for failure. The concepts of intrinsic and extrinsic motivation are handled later in this paper. Thanks to the formalization of grassroots principles, the process has shown to be sustainable in the long term. It is important to emphasize the importance of the self-coordinated and self-assembled teams, that were composed of employees from different organizational levels and functions. They were given sufficient managerial autonomy and resources to fully develop their business ideas. Last but not least, participating employees benefitted from Innospire in different ways. The management training opened up a new world for a lot of scientists and improved their competence, because they were trained in a new skill set, for example on the bootcamp. Innospire stimulated networking and relatedness among employees in several ways. They came together and discussed with colleagues from other divisions, and these otherwise rare discussions allowed them to come up with new (cross-sectional) ideas.

A similar project is Gamechanger at Shell (Hamel & Skarzynski, 2001). In 1996, Shell was suffering from an innovation deficit and was unlikely to meet its earnings targets. Providing $20 million to employees in order to fund ground-breaking new ideas was not enough to motivate employees. Shell organized ideation and action labs, where employees could discover new insights and incubate new ventures. Throughout the years, the Gamechanger process has been formalized, but the major lines along this process have remained. Nowadays, employees with a promising idea can pitch for 10 minutes, followed by a Q&A session. When the panel sees merit in an idea, the proponent gets funding of on average $100.000. Ideas that do not pass the panel are deposited in a database, which is accessible for all other employees.

Gamechanger and Innospire both are powerful synthesis of top-down and bottom-up perspectives. It’s top-down because senior management organizes this event, provides the financial resources and defines the strategic intent. It’s bottom-up because its root purpose is to help people throughout the company to transform their ideas into business value.

5.3 Other radical grassroots innovation programs In this chapter I will elaborate on radical grassroots programs at Google, Valve software, IBM and Ghent University. Albeit its strong growth, Google has always tried to maintain a smallcompany culture. Google engineers are organized in small teams with significant autonomy. Google can be seen as a technocracy, where resources and control are allocated based on the 13

quality of the projects, rather than on hierarchical status. Further on, Google technical employees are encouraged, or even required, to spend up to 20 percent of their time with their peers, working on innovative projects that they’ve thought out. These employees advertise their projects on the company’s intranet, and make a team with interested co-workers. If these projects pass an initial gate review, it can become eligible for further support and investment as an official project. The small autonomous teams can take some risks. Marissa Mayor, Google’s head of search products, estimates that around 80% of the products will ultimately fail. Due to their enormous scalability, the successful 20% can cover these costs. The only management regulation states that the software code must fit with the existing software and hardware infrastructure. Both Google Maps and Gmail were started as unofficial, employee innovations.

Valve Software is a video gaming company with around 300 employees and perhaps the most bottom-up innovation company one can imagine.2 Valve is rather unique. First, it does not have a structure, nobody is anybody’s else supervisor or manager. There are no permanent roles assigned at Valve. Different people rise to management roles on each project organically, depending on the skills needed for that project. Second, employees choose to work on projects where they think they will add the most value, where they will have the highest direct impact on customers and what leverages their individual strength most. This freedom to work also means that they can create a new project and recruit their own team. Third, hiring is the number one priority for Valve because poor hiring decisions can run unchecked for a while and may have a large negative impact. Valve encourages employees to invite their friends to come work with the thought that friends of employees will probably also fit in well with the company. Valve doesn’t even have a Human Resources department, because employees make the hiring decisions. When a potential hire leaves, anyone in the office can participate in the discussion whether he should be given a job offer. Fourth, Valve uses a project-based stack ranking system to capture the full value that each employee brings to the company. The goal is to match an employee’s pay to the value that he creates, as determined by his coworkers. There is no upper level to the end-of-year bonuses. This approach seems to work for them: in 2011, Valve announced that they are more profitable than either Google or Apple per employee. As a privately held company, they do not release financial information, but in 2012 independent analysis suggested the company is worth at least $3 billion.3

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Through IFundIT, IBM employees can submit an idea, criticize on one, invest in others or suggest improvements.4 When submitting an idea, employees set a funding target. The CIO funded $300.000 to different employees, with a maximum of $2.000 per employee. With this money, employees can invest in projects, or they can volunteer their expertise to help with others ideas. Once the funding target has been reached, the project is funded and started. This provides the company with a lot of new innovations, which value is supported by their employees. For employees, it is good because they can work on their own ideas and it’s a possible way to prove yourself in the organization. This is another clear example of ‘resource attraction’ (Hamel, 1999).

In Flanders, Alcatel-Lucent (2006), Barco (2011), BASF (2001), Jansen Pharmaceutica (2010) and Ghent University (2015) have grassroots innovation projects. The Innoversity Challenge is a project from the University of Ghent in order to harvest students’ ideas on the digitalization of education. The university’s president, Anne De Paepe, fully endorsed this program and sent an e-mail to all students to inform them about this project. At every campus, banners were hung at the main entrance to motivate students to participate. 544 innovative ideas were harvested, of which 10 were selected. These ten teams had a couple of months to fully work out their idea, in order to present it at the final jury presentations.5 These presentations took place on 3 March 2016, resulting in 4 winning teams . Their subjects were gamified learning, a class interaction promoting app, adaptable slideshows that improve the one’s made by professors and an app to easily find study and group work places in the university.6 The winning teams were given a letter of recommendation from the university’s president and a gift voucher. These 4 ideas will have a pilot project in the fall semester of 2016.

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6. Hypotheses 6.1 Dependent variables In this chapter, I will look into which factors correlate with grassroots innovation involvement in companies. First, I will summarize the dependent variables of my questionnaire. These are the maturity of the grassroots innovation process, how motivated employees feel to participate in grassroots innovations and how frequently they take initiative for incremental and radical innovations. The maturity of the grassroots innovation process depends on how accepted and promoted bottom-up is throughout the organization. The resulting variables are named ‘Maturity’, ‘Motivation’, ‘IncrementalInput’, and ‘RadicalInput’. The three last variables are strongly correlated (appendix 2.1) and I have added them together. This created the variable ‘grassroots innovation involvement’, which I will use as the dependent variable. The full questionnaire can be found in appendix 1.

6.2 Independent variables 6.2.1 Size and technology A meta-analysis shows that there is a positive correlation between firm size and innovativeness. However, the relation is rather complex, and could be influenced by several factors (Becheikh, Landry, & Amara, 2006). Small companies rank better than large firms on innovation performance (innovation output, moderated for firm size). This suggests that small companies are more efficient in their innovation efforts (Love & Ashcroft, 1999). In one study, size was negatively correlated with employee entrepreneurial behavior (Caruana, Morris, & Vella, 1998). Following (Caruana et al., 1998), I will hypothesize a negative correlation between firm size and bottom-up innovation. Innovation and technology have a significant relationship (Becheikh et al., 2006). High-tech industries are more innovative than traditional ones (Evangelista et al., 1997; Quadros et al., 2001) and innovation has a stronger effect on performance in high-tech as opposed to lowtech industries (Bierwerth et al., 2015). Thus, high-tech firms have more opportunities for innovation and have a bigger pay-off if they innovate successfully. One could hypothesize that employees in high-tech firms would be more involved in grassroots innovation.

Hypothesis 1a: Employees in bigger companies will be less involved in grassroots innovation. 16

Hypothesis 1b: Employees in high-tech companies will be more involved in grassroots innovation. 6.2.2 Qualified human resources Staffing companies with trained, highly educated, technically qualified and experienced personnel with diverse backgrounds is an important determinant of innovation (Freel, 2003, Koeller, 1996, Nelson, 2000; Koschatzky et al., 2001, Romijn & Albaladejo, 2002). ‘All these human resource strategies help companies to have a qualified and motivated workforceincluding employees, engineers and technicians, capable of creating new technologies and absorbing outside-developed ones’ (Hoffman et al., 1998; Romijn & Albaladejo, 2002). One might expect that trained, educated and experienced personnel have more knowledge of their field and thus are more likely to think about optimizations. I will test whether these three factors influence grassroots innovation.

Hypothesis 2: Trained, educated and experienced personnel will be more involved in grassroots innovation. 6.2.3 Intrinsic motivation The self-determination theory is a theory about human motivation (Deci & Ryan, 1985). Ryan and Deci made a basic distinction between intrinsic and extrinsic motivation. Intrinsic motivation refers to doing something because it is inherently interesting or enjoyable. Extrinsic motivation refers to doing something because it leads to a separable outcome, like a reward or a punishment. The former is the inherent tendency to seek out novelty and challenges, to extend and exercise one’s capacities, to explore and to learn (Ryan & Deci, 2000). From birth, healthy children are active, curious and playful without needing specific rewards (Harter, 1978). The construct of intrinsic motivation describes this natural inclination towards interest and exploration (Csikszentmihalyi & Rathunde, 1993; Ryan, 1995). Ryan and Deci assume that people have a tendency towards activity and integration, but that they are vulnerable to passivity. They examine the conditions that raise versus diminish people’s intrinsic motivation (Ryan & Deci, 2000). The cognitive evaluation theory (CET; Deci & Ryan, 1985) is a sub theory within SDT that aims to explain the variability in intrinsic motivation. It focuses on the fundamental needs for competence and autonomy. They found that people need to feel competent and autonomous, or self-determined, in order to enhance intrinsic motivation (Fisher, 1978). Optimal challenges and freedom from demeaning evaluations facilitate intrinsic motivation as it makes people feel competent. When this feeling 17

of competence is accompanied by a feeling of autonomy, intrinsic motivation will be enhanced (Ryan & Deci, 2000). Extrinsic rewards, for example money, can undermine intrinsic motivation. This can be explained due to the fact that extrinsic rewards diminish autonomy (Deci & Ryan, 1975). This was a controversial topic, but it was confirmed by a comprehensive meta-analysis (Deci, Koestner & Ryan, 1999). ‘Threats, deadlines, directives, and imposed goals diminish intrinsic motivation, because they conduce toward an external consequence. On the other hand, choice, acknowledgment of feelings, and opportunities for self-direction enhance intrinsic motivation, because they enhance a person’s feeling of autonomy’ (Ryan & Deci, 2000). Students who are taught with a more controlling approach (in contrast to an autonomous approach) lose initiative and learn less effectively (Amabile, 1996; Grolnick & Ryan, 1987). The third factor in the self-determination theory is relatedness or connectedness (figure 6.1). Intrinsic motivation is more likely to flourish in contexts characterized by a sense of relatedness (Ryan & Deci, 2000). While relatedness is not always necessary, it does seem to be important in the expression of intrinsic motivation. It is important to note that people will only be intrinsically motivated for activities that hold intrinsic value for them, activities that look novel or challenging. When those activities or not, the principles of CET do not apply. One can argue that bottom-up innovation is indeed an intrinsically interesting activity, because it is a novel and challenging task for employees. So, in order to understand motivation for bottom-up innovation, I do not need to dive deeper into extrinsic motivation.

Intrinsically motivated people have more interest and excitement, which is manifested both as enhanced performance and creativity (Deci & Ryan, 1991; Sheldon, Ryan, Rawsthorne, & Ilardi, 1997). ‘Over three decades of research has shown that the quality of experience and performance can be very different when one is behaving for intrinsic versus extrinsic reasons (Ryan & Deci, 2000).’ Intrinsically motivated employees do their job well regardless of whether they are supervised or not, they have a passion for doing something innovating (Hyppia, & Parjanen, 2013). I could hypothesize that intrinsically motivated employees will be more eager to participate in grassroots innovation. In order to measure the intrinsic motivation for employees, I will use a translated version of (Broeck et al., 2010), which has proved to be a good measure of autonomy, competency and relatedness.

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Figure 6.1: Self-determination theory

Hypothesis 3: Employees who are autonomous, competent and feel related will be more involved in grassroots innovation.

6.2.4 Company culture There is a significant relationship between ‘company culture’ and ‘innovation’ (Akkermans, Isaksen, Isaksen, 2008; Parjanen, 2012; Martins & Terblanche, 2003). I will measure a company’s innovation climate with two different constructs: Entrepreneurial Orientation (EO) and Corporate Entrepreneurship Assessment Instrument (CEAI). While the former focuses on the organization’s top-down strategy, the latter focuses on the influencing factors of employee behaviour.

First, I will describe the Entrepreneurial Orientation Scale. Entrepreneurial orientation (EO) is one of the most important and established concepts in the field of entrepreneurship. ‘It is a firm-level strategic orientation, which captures an organization’s strategy-making practices, managerial philosophies, and firm behaviors that are entrepreneurial in nature’ (Anderson, Covin, & Slevin, 2009). It is the entrepreneurial orientation of the firm itself, in contrast to its environment. The construct of EO consists of three dimensions: proactiveness, risk taking and innovativeness. Innovativeness measures the tendency to support new ideas, experimentation, and creative processes. It represents a basic willingness to start depart from existing technologies and venture beyond the current state of the art (Lumpkin & Dess, 1996). Proactiveness refers to the anticipation of future wants in the marketplace, in relation to competitors (Lumpkin & Dess, 1996). Risk-taking is associated with a willingness to commit a lot of resources to projects where the cost of failure may be high (Miller & Friesen, 1978). This suggests that companies with EO are more focused on opportunities (Wiklund & Shepherd, 2003). It is currently accepted to interview top-management about the EO of a company (Wales, Monsen, & McKelvie, 2011). 19

EO enhances firm performance and the variance in firm performance, because entrepreneurship is a risky undertaking (Wiklund & Shepherd, 2011). The effect of EO on performance is bigger high tech companies (Rauch, Wiklund, Lumpkin, & Frese, 2009). Albeit the vast literature on EO, the relationship between EO and grassroots innovation has remained unexplored for a long time (Bouchard & Basso, 2011; Todorovic, Todorovic, & Ma, 2015; Huang & Wang, 2011). EO is entrepreneurship on the firm level. Most questions refer to top management’s behavior and beliefs, while not one question refers to employees. Although prior research has clearly embraced EO as an organizational phenomenon, it has not been made clear how it is manifested throughout the organization. To date, researchers have assumed that EO pervades an organization homogeneously across all hierarchical levels and organizational subunits, without supporting this assumption (Wales et al., 2011). The pervasiveness of EO reflects how EO attitudes and behaviors are manifested throughout an organization. In this master’s thesis, I will focus on the vertical pervasiveness (from top level management to rank and file employees). I will test the assumption that entrepreneurship at the firm level implies entrepreneurship at the individual level.

Hypothesis 4: EO has a positive correlation with grassroots innovation involvement.

The second construct is the Corporate Entrepreneurship Assessment Instrument (CEAI) (Hornsby, Kuratko, & Zahra, 2002). I will use the most recent, refined version of a scale that measures the organizational preparedness for corporate entrepreneurship (Hornsby, Kuratko, Holt, & Wales 2013). It was developed to measure the key internal organizational factors that influence a firm’s employee entrepreneurial activities and outcome (Hornsby et al., 2013). This construct is targeted at middle-managers, but I will check whether it is also relevant for rank and file employees. On average, upper-middle management reported more entrepreneurial perceptions than middle and lower-middle management (Hornsby et al., 2002). To my knowledge, this study will be the first to use the renewed construct. The updated CEAI is a 18-question construct and is divided into four specific dimensions to measure the key internal organizational factors that influence a firm’s entrepreneurial activities and outcomes. These four dimensions are ‘management support’, ‘work discretion’, ‘rewards and reinforcement’ and ‘time availability’ (figure 6.2). First, ‘management support’ represents top management’s willingness to promote and facilitate entrepreneurial behavior, by championing innovative ideas and providing the necessary resources. To champion an idea 20

means that someone from middle or upper level management will help the innovative employee, when he or she would be faced with difficulties within the company. Second, ‘work discretion’ reflects top management’s commitment to tolerate failure and to provide autonomy and decision-making freedom. This is very close to the ‘autonomy’ construct from the SDT. Third, ‘rewards and reinforcements’ represents systems that reward based on performance and highlight significant achievements. Fourth, ‘time availability’ represents the participants’ perceptions regarding the workload and the ability to dedicate time toward longterm problem solving (Hornsby et al., 2013).

Figure 3.2: CEAI

Hypothesis 5a: CEAI has a positive correlation with grassroots innovation involvement. Hypothesis 5b: Management support has a positive correlation with grassroots innovation involvement. Hypothesis 5c: Work discretion has a positive correlation with grassroots innovation involvement. Hypothesis 5d: Rewards and reinforcements has a positive correlation with grassroots innovation involvement. Hypothesis 5e: Time availability has a positive correlation with grassroots innovation involvement. 6.2.5 Formalization and centralization Centralization refers to the extent to which decision-making power is concentrated at the top levels of the organization. Centralization and autonomy can be viewed as lying at opposite ends (Caruana, Morris, & Vella, 1998). Centralization is the opposite of autonomy, and is negatively correlated with grassroots innovation (Caruana et al., 1998). Formalization refers to the existence of formal rules and regulations and the organization's efforts to enforce those rules (Caruana et al., 1998). Findings regarding the effect of 21

formalization on organizational culture, particularly on innovativeness, appear to be rather mixed (Miller & Friesen, 1984). In start-ups, formalization tends to be low, due to the close personal and social relationships. When firms grow, however, these relationships tend to be lost. Formalization ensures that the company is able to sustain individual creativity in solving organizational goals without becoming dependent on centralization policies. ‘Formalization helps to ensure that individuals and teams do not, in the name of innovativeness, pursue random or superfluous opportunities that are inconsistent with the company's mission and strategic direction’ (Caruana et al., 1998). Provided that formalization is not taken to extremes, it is beneficial (Caruana et al., 1998). Some studies suggest a positive relation between innovation and formalization (Jansen, Van den Bosch, & Volberda, 2006; Caruana et al., 1998). However, ‘while formalization may normally act as a hindrance during the initiation stage of innovative behavior, it can act positively during the implementation stage’ (Zaltman, Duncan, & Holbek, 1973). Because I only measure the initiation stage of innovative behavior, I hypothesize a negative relation. I will measure centralization and formalization with (Ferrell & Skinner, 1988).

Hypothesis 6a: Centralization has a negative impact on grassroots innovation involvement. Hypothesis 6b: Formalization has a negative impact on grassroots innovation involvement.

6.3 Summary Table 6.1 depicts a summary, by repeating the hypothesized relationship between GII and the given variables. In the ‘hypothesis’ column, a ‘+’ depicts a positive expected correlation with grassroots innovation involvement, while a ‘–‘ depicts a negative expected correlation. One sign depicts an expected correlation, while a double sign, e.g. ‘++’, depicts a strongly expected correlation. This difference is based on the literature study. For example, there is a positive correlation between technology and innovation, so one might expect a positive correlation between technology and bottom-up innovation. This relation does not have a very strong foundation. On the other hand, I really expect a correlation between centralization and grassroots innovation, because this has already been found in another study, so I put ‘++’ in the ‘hypothesis’ column. In the last column, one can find the studies on which the relations are based. A summary of used constructs to measure the last 5 independent variables can be found in chapter 7.2.1.

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Table 6.1: Hypotheses

Size

Hypothesis Basis -(Caruana et al., 1998): size-grassroots innovation -

Technology Employee education Employee experience Employee training

+ +

(Evangelista et al., 1997): technology-innovation + (Nelson, 2000): education-innovation +

+ +

Intrinsic motivation

++

EO CEAI

+ ++

Centralization

--

Formalization

--

(Romijn & Albaladejo, 2002): experience-innovation + (Nelson, 2000): training-innovation + (Deci & Ryan, 1985; 2000): SDT- performance & creativity + (Hyppia & Parjanen, 2013): SDT- innovative employees + (Wales et al., 2011): Assumption of this relation (Hornsby et al, 2013): CEAI-grassroots innovation + (Caruana et al., 1998): centralization-grassroots innovation (Zaltman et al., 1973): formalization-innovation initiation -

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PART 2: RESEARCH

7. Methodology 7.1 Pretesting I made my survey on the basis of existing constructs for the independent variables, but used my own questions to measure the dependent variables. My dissertation advisor helped me to refine my questions and to put the survey in a more logical order. After this fine tuning, I send my questionnaire to 6 employees by e-mail, who gave me feedback. Most questions were clear and I adjusted those questions who were not clear enough. After this, I could upload my questions in Qualtrics, a research platform, provided to me through the Marketing department of the Faculty of Economics of the Ghent University. In Qualtrics, I had to make sure that questions have to be answered and that my questionnaire was as user-friendly as it could be.

7.2 Survey 7.2.1 Structure This chapter is a short explanation of the structure of my survey. The survey itself can be found in appendix 1. I started with a small introduction about myself and my research. On the first page, I provided personal details in case respondents had any questions and stated that filling out the questionnaire should take around 10 minutes. On page 2, I provided an introduction to grassroots innovation and different examples. After this introduction, I started by measuring the dependent variables. A small text about the difference between incremental and radical innovations followed. Afterwards, I asked them how frequently they take initiative with an incremental and radical idea respectively. The next question was how often they guessed their colleagues took initiative with an incremental and radical idea respectively. Following this, I questioned the independent variables. The first question was how much time per week they had to work on developing their own ideas, followed by a translated version of (Miller/Covin and Slevin, 1989) in order to measure EO. This was followed by a translated version of (Van den Broeck et al., 2010) to measure SDT, the CEAI (Hornsby et al., 2013) and a translated version of (Ferrell & Skinner, 1988) to measure centralization and formalization respectively. These existing constructs were all measured on 5 (SDT) to 7 (others) point Likert scales. Finally, I asked them some demographic (age, sex, education and

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experience) and company related (number of employees, government, sector, department, managerial level) questions. 7.2.2 Distribution I distributed my questionnaire online, through the link that was provided by Qualtrics and through a paper version. I sent the link to Qualtrics to family members and other close people, but I preferred handing out the paper version in general, because it puts more pressure on the respondents to fill out the questionnaire. Further, I also followed the random walk method (Wijnen, Janssens, De Pelsmacker & Van Kenhove, 2002) to get extra surveys. The directives of this random walk method were to visit every second house and turn left at an intersection, unless this meant I returned to a previously visited street. If somebody was at home, I introduced my survey to them and asked if they wanted to participate, stating that I would pick it up again in a week. I distributed my survey in Veurne, Diksmuide and Meulebeke. 7.2.3 Demographics My survey was online on Qualtrics from 17 March 2016 until 12 April 2016. During this period, 147 people opened the link, of which 19% dropped out, resulting in 119 complete answers. After reverse scoring, I had to delete 14 inconsistent questionnaires. This left me ultimately with 105 good quality answers. The demographics of the respondents and their companies can be found in table 7.1. ‘Hogeschool’ is a Belgian non-university institute for post-high school education. The courses are more practice oriented than at a university.

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Table 7.1: Demographics of respondents

Sex

Male Female

57,1% 42,9%

Age

18-30 31-40 41-50 51-60 60+

39,0% 18,1% 15,2% 26,7% 1,0%

Number of employees

0-49 50-1000 1000+

38,1% 33,3% 28,6%

Government

Yes No Semi

17,1% 76,2% 6,7%

Highest degree

High school/0 ‘Hogeschool’ University

20,0% 41,0% 39,0%

Number of subordinates

0-5 6-25 26-75 75+

79,0% 15,2% 3,8% 1,9%

Sector

Low tech Mid tech High tech

28,6% 59,0% 12,4%

There is an overrepresentation of younger people, because my random walk started in urban areas known for the fact that a lot of young people reside there. Further, I asked nephews, nieces and friends who work to arrange 2-3 respondents. They have asked people close to them, which are more likely to be their same age. My survey was mainly targeted at lower level employees, so it is positive to see that almost 80 per cent commands less than 6 employees, and 95 per cent commands less than 26 employees. The ‘low tech sector’ concerns government, non-profit, nursing, transportation, mailing and education. The ‘mid tech sector’ concerns different production sectors like clothes, food and metal, and the financial sectors. The ‘high tech sector’ concerns chemical, consultancy, ICT and R&D companies. 7.2.4 Descriptives The majority of respondents describes the grassroots innovation maturity in their company as ‘low’ or ‘average’ (figure 7.1). Only a couple of outliers have no possibility to innovate or work at intrapreneurial companies. Most employees feel motivated to innovate or feel neutral (figure 7.2). As expected, radical innovations happen a lot less frequently than incremental innovations (figure 7.3).

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Figure 7.1: Grassroots maturity

Figure 7.2: Innovation motivation

Figure 7.3: Incremental and radical innovation

The Cronbach’s alpha (Cronbach, 1951) for all scales were tested and the constructs were found to be internally consistent, with Tabel 7.2: Descriptive of scales Cronbach Construct Average alfa 0,887 31,59 EO

between 0.7 and 0.95 (table 7.2; appendix 2.2).

Max

Stddev

#questions

9,00

59

11,15

9

Scale (5-7 point) 7

Min

Avg/question 3,51

Connected

0,846

23,84

12,00

30

4,6

6

5

3,97

Competence

0,865

25,06

10,00

30

3,697

6

5

4,18

Autonomy

0,852

23,1

5,00

34

6,76

5

7

4,62

TimeAvail

0,703

18,48

7,00

31

5,618

5

7

3,7

MngSupp

0,855

18,13

5,00

34

6,997

5

7

3,63

Rewards

0,814

11,65

3,00

21

4,917

3

7

3,89

Form

0,739

20,7

7,00

35

6,349

5

7

4,14

Cent

0,891

21,01

7,00

35

7,584

5

7

4,2

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There is a strong correlation between the grassroots innovation process maturity on the one side, and employees’ contentedness with this maturity, their motivation to participate and their involvement (appendix 2.3: t=.64**;t=.487**;t=.353** resp.). Following (Åmo & Kolvereid, 2005), managers are more involved in grassroots innovation than rank and file employees (p=.048 and p=.000 resp.).

8. Analyses, results and conclusion To check for correlations, I will use Kendall’s tau, because the variables of innovation input and motivation are measured on an ordinal scale. When using t-values, I will use * to indicate that p