A study on the effect of various employee involvement practices on company innovation, including the moderation role of workplace autonomy.
Thesis MSc Business Administration Leadership and Management
University of Amsterdam, Amsterdam Business School Supervisor: dhr. dr. A. Pircher Verdorfer
January 15, 2021
Kimme Smit (12466433)
Involving employees in organizational decision-making becomes more and more important (Rohlfer, 2018). Such involvement practices often function as strategic drivers to increase performance, motivation, innovation, and organizational efficiency (Smith, Wallace, Vandenberg & Mondore, 2018). This study examines various employee involvement
practices and their influence on different categories of company innovation, as well as the role of workplace autonomy as potential moderator. This research contributes by filling three gaps: analyzing employee involvement data on an organizational level, comparing different involvement programs, and analyzing boundary conditions within the work environment. A quantitative analysis has been conducted based on data from the European Company Survey 2013. By running logistic regressions and adding the necessary controls and fixed effects for country and industry differences, new insights were reached. Employee involvement in the form of regular meetings, suggestion schemes, and information dissemination have a positive effect on innovation at the company level. This study found no evidence for workplace autonomy to be as a moderator in strengthening this relationship. These results can serve as a steppingstone for further research into what involvement practice is most beneficial, and what other workplace conditions might affect the effects of such practices.
I am very grateful for the time and the constructive and valuable feedback of my supervisor A. Pircher Verdorfer. Next to that, I would like to thank Eurofound for constructing the European Company Survey and the UK Data Archive for providing the dataset and granting me access to the data. Finally, I thank my Amsterdam roommates for putting up with me during the many (late) hours at home, due to COVID-19, while executing this study.
Statement of originality
This document is written by Kimme Smit 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 the work, not for the contents.
Table of contents
1. Introduction 5
2. Literature Review 9
2.1 Employee involvement 9
2.1.1 What involving employees means 9
2.1.2 Benefits of employee involvement 11
2.2 Company innovation 11
2.2.1 Innovation categories 11
2.2.2 Why innovation (usually) brings success 13
2.3 Workplace autonomy 13
3. Hypotheses Development 15
3.1 Employee involvement and company innovation 15
3.2 Three different employee involvement practices 16
3.3 Moderator effect of workplace autonomy 18
4. Methodology 20
4.1 The European Company Survey 2013 20
4.2 Descriptive statistics 26
4.3 Measures 26
4.3.1 Dependent variable companyinnovation 26
4.3.2 Independent variable employeeinvolvement 28
4.3.3 Moderator variable workautonomy 30
4.3.4 Control variables 30
5. Results 32
6. Discussion and conclusion 37
6.1 Summary of main findings 37
6.2 Implications 38
6.3 Limitations 41
6.4 Future research opportunities 42
Organizations must continuously adapt to the changing environment and they are always on the lookout to grow their base of employees who frequently advance their work climate and are looking for innovative opportunities (Rank, Pace & Frese, 2004). Even though individual attributes are important for employee thriving, aspects of the work environment are essential as well (Spreitzer, Sutcliffe, Dutton, Sonenshein & Grant, 2005). In order to keep up with competition and maximize organizational effectiveness, employee involvement has become a field of great importance (Judeh, 2011) and is a popular studied topic in academic
This research aims to contribute to three identified research problems. First, many studies have found a positive relationship between employee involvement and various organizational aspects like job satisfaction (Zatzick & Iverson, 2011; Cox, Zagelmeyer &
Marchington, 2006) or overall productivity (Zwick, 2004; Miller & Monge, 1986). These studies mainly focus on employee involvement on an individual level. Less is known about employee involvement on a company level; which is the first gap addressed in this study.
Second, not much research has been done regarding the difference in benefits between various involvement practices, in spite of their multilateral benefits, especially not in relation to company innovation. This is confirmed by Marchington & Kynighou (2012) who address that many studies discuss employee involvement practices in general, without making a distinction between the specific form of practice that is under investigation or has been implemented. A gap in the literature exists in research being done on different involvement programs in organizations (Smith, Wallace, Vandenberg, & Mondore, 2018).
Third, the value of most organizational approaches is marked by certain boundary conditions that either limit or stimulate the effectiveness of the approach (Richardson, Vandenberg, Blum & Roman, 2002). The behavior of employees is (partly) based on the
environment in which they work (Wallace, Butts, Johnson, Stevens & Smith, 2016).
Understanding this work environment and its characteristics, which influence the
effectiveness of organizational practices, is crucial. Currently, we know little about these boundary conditions, which compromises the third gap addressed in this research.
This study will contribute to the literature by narrowing the gap of examining different employee involvement programs, discussing employee involvement on a company level (with subsequent data derived at a company level), and by studying workplace autonomy as
potential boundary condition in the relationship between various employee involvement practices and company innovation. It is important to address these gaps and gain more knowledge on employee involvement as it is positively related to various company outcomes as job satisfaction (Lambert, Minor, Wells & Hogan, 2016), performance and productivity (Alazzaz & Whyte, 2015; Mazayed et al., 2014), and the ability to sustain a competitive advantage and respond to organizational change (Bayraktar, Araci, Karacay & Calisir, 2017).
Amah & Ahiazu (2013) find that employee involvement positively affects aspects of overall organizational effectiveness, which makes it logical as well as necessary to measure
involvement on an organizational level. Furthermore, analyzing involvement on a group level is important as individual perceptions are subjective and might cause biases. Measuring involvement on a group level therefore provides a much wider understanding of what makes structural or organizationally anchored involvement effective and causes results to be more widely applicable when aiming to implement involvement practices in organizations. Lawler (1992) states that successful involvement starts at the management and immediate supervisor level. The results of this study will be relevant to organizations as they can guide managers on how to successfully manage the workforce and fully utilize their employees’ knowledge and capabilities. The results can also be used to train managers on the importance of employee involvement and how to reap the highest benefit from involvement practices (Smith et al.,
2018). Moreover, this study is relevant for organizations that aim to enhance their
performance and gain more insights on what involvement practices are worth investing in.
Another aspect that contributes to a wider understanding and applicability of the findings of this study is the fact that various employee involvement practices are taken into account. This helps organizations decide on what practice is best suitable for their business and which accompanying outcomes are most in line with their objectives. Wegge et al. (2010) state that how various forms of organizational participation can be beneficially put into practice, remains a challenging question. Finally, according to Spreitzer et al. (2005) it is important to recognize the characteristics of the workplace environment that serve as boundary conditions on certain organizational approaches as they affect the extent to which employees thrive.
Many studies explored the ultimate work design and steadily find that letting employees participate in (important) work-related decisions and providing them high autonomy results in better overall performance and enhances employees’ wellbeing (Wegge et al., 2010).
Workplace autonomy is therefore considered an interesting boundary condition to study.
Moreover, from a practical/business perspective, workplace autonomy is interesting to study since it is a concept that is directly influenceable by an organization. Studying this workplace parameter has therefore a clear application for businesses. It provides insights into how workplace autonomy can act as a means for organizations that aim for the maximization of their innovative output through the implementation of involvement practices. To the best of my knowledge, workplace autonomy has not been studied in the literature as a moderator for employee involvement and company innovation.
Overall, this study aims to confirm the general recognition in the extant literature that engaging and involving employees in organizational practices is now even more important than in the past (Baldev & Anupama, 2010; Rohlfer, 2018). Strategies on employee
involvement have reached global presence in organizations over the years (Su & Wright, 2012), which makes it needed to extend research in this area.
This study aims to fill the four gaps as mentioned above by examining the effect of three different employee involvement practices; (1) meetings between employees and immediate managers, (2) dissemination of information, (3) suggestion schemes, gathered at the company level, on company innovation. Workplace autonomy is examined as a potential boundary condition because it is expected that for high levels of workplace autonomy, the relationship between employee involvement and company innovation is strengthened.
Subsequently, the main research question of this paper is: How do different employee involvement practices influence company innovation and is this moderated by workplace autonomy?
This research is the first to use the European Company Survey (ECS) 2013 dataset to examine the effect of employee involvement on company innovation. All variables are analyzed on an organizational/group level.
This paper is organized into six sections. It begins with the introduction. Second, a literature review on employee involvement, company innovation, and workplace aut onomy is given. The third section covers a theoretical background and substantiates the subsequent hypotheses. Section four discusses the methodology, data, and variable descriptions. The fifth section describes the results. The sixth section contains the main findings, limitations of the study and some possibilities for future research. The paper ends with a brief conclusion.
2. Literature Review 2.1 Employee involvement
2.1.1 What involving employees means
There are various definitions of employee involvement used in the literature. Neirotti (2018) states that employee involvement refers to “the degree to which workers participate in making decisions about their jobs and working conditions” (p. 4). Benson & Lawler (2016) argue that employee involvement in general has to do with “a call for decision‐ making power,
incentives for employees to take responsibility for their performance, skill development, the provision of information to make decisions, and job security” (p. 6). In general, it addresses the extent to which employees are engaged and committed to contributing to organizational practices.
Wegge et al. (2010) identify three different types of employee involvement in organizational leadership; organizational democracy, shared leadership, and organizational participation. Organizational democracy is the most intense form of employee involvement and constitutes an organizational atmosphere in which employee participation is centralized and institutionalized. Shared leadership is ‘‘a group process in which leadership is shared among, and stems from, team members’’ (Pearce & Sims, 2002, p. 172) and leadership is seen as a ‘‘collaborative, emergent process of group interaction whereby group members jointly enact leadership functions while working together’’ (Pearce & Conger, 2003, p. 53).
Finally, organizational participation describes how principals (managers) share decision- making power and authority with their agents (employees). In general, it means that at least more than one person works together with others on developing plans or making decisions (Wegge et al., 2010).
This study focuses on the organizational participation type of employee involvement and studies three different practices within organizational participation regarding how work is
organized in different fields. The first practice studied focuses on interaction and
communication between different levels in the organization and measures whether there are regular meetings between employees and their immediate managers (Marchington &
Kynighou 2012). Lawler (1996) identified that for employee involvement to be effective, it must include some crucial features, one of which is the flow of information. He states that communication is key. Therefore, the second practice assesses the dissemination of information through various channels (newsletters, website, notice boards, email) as
mentioned by Marchington & Wilkinson (2005), which increases employees’ knowledge and the transparency of information flows. The third practice includes suggestion schemes. It is important to focus on employees’ idea contribution as it could add value to the organization (Yang & Konrad, 2011). Back in the old days, there used to be an old -fashioned mailbox in company’s hallways where employees could leave their ideas. Currently, we use online suggestion systems (van Dijk & van Den Ende, 2002). The benefits of suggestion systems increased; online versions are easy in approach and use, and efficiency in the entire idea generation and development process is boosted (Abu El-Ella, Stoetzel, Bessant & Pinkwart, 2013). This employee involvement practice has also been identified by Eccles (1993) and is studied here as the third and final practice. It shows employee involvement through
suggestion schemes, i.e. the collection of ideas and suggestions from employees, voluntary and at any time, traditionally by using a (digital) ‘suggestion box’ (Delery & Shaw, 2001;
Pfeffer, 1998). Involvement through suggestion schemes works in a way that encourages employees to hand in ideas and contribute their input, while management keeps the final decision-making power (Bowen & Lawler, 1992).
2.1.2 Benefits of employee involvement
The extent to which employees are involved in organizational practices is often studied in the context of high-involvement work processes (Boxall, Hutchison & Wassenaar, 2015). Attention is devoted to involving employees in work processes as it strengthens the ability of an organization’s workplace (Appelbaum, Bailey, Berg & Kalleberg, 2000).
Employee involvement is also regarded as a crucial driver of organizational effectiveness (Bosak, Dawson, Flood, Peccei, 2017). More specifically, it encourages employees’ personal development and responsibility, it stimulates voice behavior, and employees who are
encouraged to think along regarding (important) decisions tend to make more of an effort and contribute to the company as a whole (Lawler, 1986).
Benson & Lawler (2016) argue that in line with traditional motivation theory,
involving employees will result in higher levels of effort and more efficient working ways. It is found that employees who are involved in decision-making are overall more productive, and they tend to be more engaged to the company objectives (Mackie, Holahan & Gottlieb, 2001). Furthermore, recognizing the importance of employee involvement is according to Manojlovich & Laschinger (2002) a crucial predictor of employee behavior at work and therefore vital for managers to take into account. The range of employee involvement varies a lot and can take on different forms, levels, and subjects (March & Wilkinson, 2000). It can diverge from extensive involvement in overall decision-making to the simple allocation of information to employees (Lopes, Calapez & Lopes, 2017).
2.2 Company innovation 2.2.1 Innovation categories
The concept of innovation mainly originates in the studies of Schumpeter, who argues that innovation arises when someone (an entrepreneur) makes new combinations that bring about
a new process, product, market, or business structure (Schumpeter, 1934). Despite
entrepreneurs usually being the drivers of new idea generation and creativity, in many cases they do not possess the qualities required for the subsequent production processes or for bringing the concept to the market (Ferreira, Fernandes & Ferreira, 2019). This leads to managers stepping in during the crucial phases of bringing the concept to life (Harryson, 2008; Hill, 2001).
This study measures the effect of employee involvement on company innovation based on European-wide data and aims to analyze whether the results of previous studies, that found a positive relationship between involvement and innovation (Wallace, Butts, Johnson, Stevens & Smith, 2016), can be confirmed. This study does not take into account innovation or creativity on the individual level. The ECS 2013 dataset measures innovation at the organizational level. Two main (organizational) innovation categories can be distinguished;
technological and non-technological innovations. Technological innovations include
product/service or product innovation, whereas non-technological innovations are for example new marketing methods or ways of communication and changes in the organization overall (Mohnen & Hall, 2013). Each category is shortly discussed. Product innovation describes the introduction of a product or service that is different from existing ones regarding its aspects or proposed use, process innovation is “the implementation of a new or significantly improved production or delivery method” (p. 48), marketing innovation is introducing a new marketing approach that is significantly different from the four p’s in the current approach
(product/packaging, price, placement or promotion), and finally, organizational innovation is the introduction of a new business method in the general practices of the company or its external connections (Mohnen & Hall, 2013). Note, these forms of innovation are not mutually exclusive. These four innovation categories are recognized by the OECD’s Oslo Manual (2005) and accordingly studied in this research.
2.2.2 Why innovation (usually) brings success
In the current complicated and competitive business environment, innovation is (one of) the most crucial factors for an organization’s prosperity and continuity as it depicts the future chances of success (Rajapathirana & Hui, 2018). According to Adhikari, Choi & Sah (2017), innovation is essential for the success of almost every organization. This is the case because innovation is regarded as a significant driver for competitive advantage, which automatically contributes to a company’s success (Crossan & Apaydin, 2010). Innovation does not only stimulate competitiveness, it also increases economic growth (Zhong, 2018).
Innovation is encouraged by transparency (Zhong, 2018) which is part of the second employee involvement practice this research examined; the dissemination of information. It will thus be interesting to see whether which employee involvement practice has a larger effect on innovation compared to the other practices.
2.3 Workplace autonomy
Workplace autonomy is “the extent to which the job provides employees with freedom and independence over their work schedules and processes” (Gagné & Bhave, 2011, p. 3). It describes the amount of work control employees are handed, for example how (and when) to carry out tasks (Parker, Axtell & Turner, 2001), and their opportunities in making their own decisions on work-related issues (Karasek, Brisson, Kawakami, Houtman, Bongers & Amick, 1998). It is studied here as an objective feature of the work context, rather than individual felt autonomy, and is seen as a critical driver for many (organizational) outcomes (Humphrey, Nahrgang & Morgeson, 2007).
Autonomy increases employees’ sense of responsibility within their work and is therefore found to be a significant predictor of creative work involvement and promoting idea generation and development (Langfred & Moye, 2004; Unsworth & Clegg, 2010). Autonomy
is also an important driver of innovation (Zhang & Bartol, 2010; Anderson, Potočnik & Zhou, 2014). Ramamoorthy, Flood, Slattery & Sardessai (2005) show a clear effect of workplace autonomy on the level of creativity experienced and disseminated by employees. Shalley, Gilson, & Blum (2000) confirm that the level of autonomy employees experience in their job increases innovative work behaviors. The level of workplace autonomy is also positively related to innovation at work (Hammond, Neff, Farr, Schwall & Zhao, 2011; Slåtten &
Mehmetoglu, 2011). Unsworth & Parker (2003) have found the same and state that work autonomy stimulates innovation.
The more employees are given responsibility and are in control of their work tasks, i.e.
the higher the autonomy handed to them, the more upward and downward communication will take place and vice versa (Lopes, Calapez & Lopes, 2017). If managers let employees engage in decision-making and transfer knowledge and power to them, employees experience more control over their jobs, and they perceive higher levels of work autonomy (Timming, 2012).
3. Hypotheses Development
In this section I develop five hypotheses about the relationship between the three variables of interest. These hypotheses are based on both theoretical reasoning and on evidence from previous academic literature.
3.1 Employee involvement and company innovation
I expect that employee involvement will be positively related to company innovation. The theoretical rational behind this expectation builds on competitive advantage and engagement.
Every organization strives for some type of competitive advantage, to outplay their rivals.
Innovation is one of the most important sources for competitive advantage (Andries &
Czarnitzki, 2014). Creating a competitive advantage through innovation requires (the exploitation of) human capital (Hitt, Bierman, Shimizu, & Kochhar, 2001). Understanding how and when employees contribute to company innovation is therefore relevant. This is often enabled by what William Kahn defined as the engagement theory. Kahn (1990) states that employee engagement is facilitated by meaningfulness, safety, and availability. These are in turn to some extent encouraged by involving employees in organizational practices beyond their daily tasks, e.g. decision-making processes. Thus, if organizations have employee involvement practices in place, employees’ engagement will increase, employees will exert extra effort next to their standard tasks, and their knowledge and skills will contribute to company innovation. This helps the organization to create or sustain a competitive advantage.
There is evidence from previous research showing that involvement has a positive effect on innovation. Datta, Guthrie & Wright (2005); Hayton (2003); Rangus & Slavec, (2017) show that an organization’s innovative performance is positively related to the extent to which responsibilities are being assigned and the extent to which employees are engaged in decision-making processes, i.e. their level of involvement. Dorenbosch, van Engen &
Verhagen (2005) find that employee involvement and commitment have a positive influence on the willingness of employees to engage in (on-the-job) innovations. Andries & Czarnitzki (2014) state that high degrees of involvement, i.e. engaging employees in decision-making and collecting their ideas, is highly and positively related to a company’s innovative performance. Employee involvement stimulates a wide range of new idea formations that foster innovation (Delery & Shaw, 2001).
The relationship between employee involvement and innovation is (partly) caused by empowerment and engagement. Yang & Konrad (2011) state that practices of employee involvement empower and engage workers, which subsequently leads to the active
participation of employees in the creation of new ideas and insights, which on its turn results in higher levels of innovation. Employee engagement is defined as “the cognitive, emotional, and behavioral energy an employee directs toward positive organizational outcomes” (Shuck
& Wollard, 2010, p. 103). Engagement and empowerment are (one of) the underlying mechanism(s) of the relationship between employee involvement and company innovation.
Based on the above theoretical and empirical reasoning, the first hypothesis states:
H1: Employee involvement is positively related to company innovation
3.2 Three different employee involvement practices
Three sub-hypotheses result in the second, third and fourth hypotheses. They test the effect of the three involvement practices on company innovation and are analyzed in model 2. They are all based on the reasoning of H1, namely through engagement and competitive advantage creation by the company. Limited research has been conducted on these three specific involvement practices. Some empirical evidence exists; however, it is quite limited. This research will be the first to study the effect of these involvement practices on company innovation.
Michie & Sheehan (1999) find that letting employees participate, i.a. meaning that they are involved in meetings every now and then, is positively related to the probability of innovating. I expect that meeting with a supervisor from time to time will increase
employees’ feelings of being appreciated, as their supervisor takes time for them and listens to them. This enhances engagement and is expected to positively contribute to company innovation. This leads to the first sub-hypothesis.
H1a: Employee involvement in the form of regular meetings between employees and their immediate manager has a positive effect on company innovation
Involvement through information dissemination is studied. If an organization informs employees frequently regarding organizational subject matters, news, concerns or by
providing knowledge, transparency increases. Yang & Konrad (2011) find that involving employees through increasing their knowledge, e.g. by enhancing information flows, fosters company innovation. Based on this, the second hypothesis is formulated.
H1b: Employee involvement in the form of dissemination of information has a positive effect on company innovation
It is shown that suggestion schemes through which employees can leave ideas, as a form of engaging and involving them, stimulate innovative outcomes (Bason, 2010).
According to Rangus & Slavec (2017), a company’s innovative performance is enhanced by employee involvement through incorporating their suggestions in idea generation. Based on these findings, it is expected the implementation of suggestion schemes as employee
involvement practice to positively influence company innovation. This leads to the following hypothesis.
H1c: Employee involvement in the form of suggestion schemes have a positive effect on company innovation
3.3 Moderator effect of workplace autonomy
The role of workplace autonomy as a moderator is studied. It is expected that workplace autonomy moderates the positive relationship between involvement and innovation, in that it strengthens this relationship. This expectation is partly based on the social exchange theory and on theories of engagement and findings from previous studies.
Input and motivation from employees depend on how they perceive the organization and feel they are, or aren’t, part of it (Wayne, 1997). This is in line with the social exchange theory that describes that “voluntary actions of individuals are motivated by the returns they are expected to bring from others…” (Gould-Williams & Davies, 2005, p. 4). Innovative output is often not part of the daily task set of employees. Moreover, it often requires
something extra. For employees to go beyond their standard activities, some support and faith is required (Gould-Williams & Davies, 2005). Organizations can provide this by for example giving employees responsibility. One way to do this is to increase employees’ autonomy in executing tasks. If managers don’t monitor employees all the time and let them freer, employees will be more eager to do something in return. This is what the social exchange mechanism predicts. The organization provides autonomy in the workplace and thereby shows trust in its employees. In turn, employees aim to reciprocate this behavior, they feel more committed and motivated, and will exert additional effort that can stimulate innovative output. In this way, positive social exchange is beneficial for both the organization as well as the employee (Gould-Williams & Davies, 2005).
Evidence from previous research shows that employee involvement practices foster company innovation through empowerment and engagement of workers (Yang & Konrad, 2011). How effective such an approach is, depends on the workplace boundary conditions (Richardson, Vandenberg, Blum & Roman, 2002). Moreover, the amount of autonomy employees experience in their job is positively related to their level of engagement towards
the company (Xanthopoulou, Bakker, Demerouti, & Schaufeli, 2007; Hakanen, Bakker, &
Schaufeli, 2006). This is confirmed by Malinowska, Tokarz & Wardzichowska (2018) who state that autonomy is a crucial workplace context feature to study as it is part of outstanding theories of work characteristics (Karasek Jr, 1979; Hackman, 1980) and it promotes (work) engagement and empowerment.
Autonomy is perceived as a significantly important workplace condition and it directly affects one of the mechanisms (engagement/empowerment) ground for the relationship
between employee involvement and company innovation. Therefore, autonomy is an interesting aspect to study as a moderator variable (Karazsia, Berlin, Armstrong, Janicke &
Darling, 2014). Moreover, some studies acknowledge the value of workplace autonomy as a moderator in organizational settings. For example, Song, Uhm & Kim (2012) claim that workplace autonomy is a moderator for creativity in a school context. In this study, workplace autonomy is treated as an essential determinant that affects the relationship between
involvement and innovation. Employee involvement practices might stimulate company innovation, but it is expected that this effect will be even larger when employees are triggered to think about the relevance of creative thinking which, according to Jaiswal & Dhar (2017), demands responsibility and autonomy in their work. When involvement practices go hand in hand with high work autonomy, the amount of company innovation may considerably increase. This results in the second hypothesis, tested in model 3.
H2: Workplace autonomy positively moderates the expected positive relationship between employee involvement and company innovation in that it strengthens this positive
This study tests the five different hypotheses as mentioned above, and as depicted in the research model in figure I. For the mathematical regression specifications of the models, see appendix section 2 part 1.
Figure I: Resea rch model with the dependent, independent, a nd modera tor va ria ble.
4.1 The European Company Survey 2013
This research conducts a quantitative research approach to study the relationships between the three variables of interest. The European Company Survey 2013 dataset is used, in line with previous studies that examined workplace systems and processes (Addison &
Teixeira, 2019; Riva & Lucchini, 2018). The 2013 survey investigates “workplace practices with regard to work organization, human resource management practices, employee
participation, and social dialogue” (Eurofound, 2015). This survey is the third wave and aims attention at matters regarding employee participation, innovation in the workplace, and workplace organization (Eurofound, 2015). The data is collected by the European Foundation for the Improvement of Living and Working Conditions (Eurofound). It is a cross-sectional dataset and consists of a management questionnaire and an employee representative
questionnaire. There is a separate dataset for both questionnaires. I have chosen to use the management questionnaire dataset as that one covers a larger sample and contains more in- depth information on company innovation and employee involvement.
Responses from 32 countries in total, including all 28 EU Member States, Iceland, the Former Yugoslav Republic of Macedonia, Montenegro and Turkey have been collected (Eurofound, 2015). The number of responses per country varies from 300-1650 and depends
on country size. The ECS 2013 data is managed by the UK Data Service Centre (University of Essex, Colchester). After registering on their website, the questionnaire was available for download in STATA format.
The ECS dataset includes data from organizations in various sectors with at least ten employees, excluding establishments in agriculture, activities of households as employers and activities of extraterritorial organizations (Eurofound, 2015). In each country, establishments were randomly selected. Surveys are conducted by telephone interviews and are held with the senior managers in charge of personnel for each establishment. In total 30,113 interviews with managers have been collected.
This study assesses and analyzes all data on an organizational level. The dataset contains responses from managers who answer the questions on behalf of their
department/group, rather than the functioning of individual employees. For example,
employee involvement and company innovation are measured on an organizational level (no individual performance measures are included) and workplace autonomy is measured on a team/group level.
I am going to test my hypotheses by running logistic regressions, as company innovation (my dependent variable) is a binary variable. The responses ‘don’t know’, ‘no answer’ and ‘.’ (which take on values 8, 9) are eliminated for all questions on innovation and employee involvement. This is uninformative data, and it could bias the value of the variables on company innovation and employee involvement, because they are constructed based on the different categories, which can lead to distorted results. The responses ‘don’t know’ and ‘no answer’ are dropped for the variables workautonomy, gender, education, and parttime as well.
For example, because 5,732 of the 27,019 responses are missing for workautonomy, which could lead to unstable estimates. The final sample consists of 18,207 responses.
Causality cannot be proven due to the selection bias of individuals into the employee involvement practices, as perfect randomization cannot be validated. All the necessary
controls (see section 4.3) are included in the regression models, in order to minimize this bias.
Intercorrelation between the independent variables and the control variables is measured for each model1 to exclude the problem of multicollinearity. The variable employeeinvolvement variable is significantly correlated with the variables for the various employee involvement practices. Because it is constructed out of those variables, it does not impose any problems. Furthermore, the interaction term is not taken into account as that one is highly correlated in advance. Besides those intercorrelations, the correlation of greatest magnitude is those between the variables gender and parttime and takes on a value of 0.25.
Robust standard errors are included in all regressions, to avoid heteroskedasticity.
Industry and country fixed effects are included in this analysis, following Crowley &
McCann (2018). Industry fixed effects are important to include as industry variation that has not been explained by the independent variables could cause biases (Buddelmeyer, Jensen &
Webster, 2010). Omitted variable bias could occur due to unobserved heterogeneity.
Industry dummies are necessary to include as there are systematic differences in the implementation of employee involvement practices per industry/sector, as becomes clear in figure II.
Figure II: Direct employee pa rticipa tion, by esta blishment size a nd sector (%), source: Eurofound (2015).
Differences also occur regarding the category of company innovation that is introduced per industry/sector, as depicted in figure III.
Figure III: Introduction of new or improved products, processes a nd ma rketing methods, a nd orga niza tiona l cha nge, by sector (%), source: Eurofound (2015).
The implementation of employee involvement practices varies substantially across the examined countries; therefore, country fixed effects are included as well (see figure IV). This could for example be the result of (company) cultural differences. If this is not controlled for, it could lead to biased results.
Figure IV: Direct employee pa rticipa tion, by country (%), source: Eurofound (2 015).
Finally, it has been tested whether multilevel modeling is necessary for this study as the outcome variable (company innovation) might be affected by group membership through respondents (managers) being clustered in countries. This is important to examine as
managers being nested in the same country might be more likely to function in similar ways compared to managers nested in other countries (Sommet & Morselli, 2017). In order to know whether multilevel modeling is needed, an intraclass correlation (ICC) test has been performed. “The ICC quantifies the degree of homogeneity of the outcome within clusters”
(Sommet & Morselli, 2017, p.212). There are three forms of the ICC: ICC1, ICC2, and ICC3.
The ICC1 is most applicable in this case since it measures a one-way random effects model, and I am interested in one type of group membership (country), and because each subject (organization) is rated by a different set of randomly chosen raters (managers) (Weir, 2005).
The ICC2 and 3 are not suitable for this study as the ICC2 is used for two-way random effects models in which the same raters with identical characteristics measure each subject and the ICC3 in the case of a two-way mixed model where the raters are fixed and when they are the only raters of interest (Weir, 2005), both not the case in this study. The ICC takes on a value between 0 and 1. If the ICC equals 0 this means that the residuals are perfectly independent of each other and outcomes are not correlated and affected by the cluster they belong to. If the
ICC equals 1 this indicates that the residuals are perfectly linked, and outcomes are purely based on cluster differences.
The ICC has been calculated for the outcome variable companyinnovation. It takes on a value of 0.0462 and is significant at a 5% level. This shows that 4,6% of the chances that innovation is present in organizations is explained by differences between countries. Koo &
Li (2016) indicate an ICC value below 0.5 indicate poor reliability. Therefore, as the ICC value of 0.046 is so small, the residuals are almost perfectly independent. This means that innovation is not likely to depend on cluster (country) membership (Sommet & Morselli (2017), and in this case can be neglected. In addition, there are two theoretical arguments for why multi-level modeling is not needed for this study. First, Sommet & Morselli (2017) stress that a multilevel logistic regression estimates the odds of the outcome variable happening for a participant i in a specific cluster j. This study aims to predict the log-odds of innovation for organization i, and not for organization i in a specific country j. Moreover, this study aims to analyze organizations regardless of their country of residence; countries are not under
investigation and differences between them are controlled for by adding country fixed effects.
Second, my research includes one level-1 predictor, namely employee involvement. It does not include any level-2 predictors; i.e., variables that do not vary within clusters (country- specific characteristics).
Based on the above theoretical and statistical reasoning, I conclude that group effects are not likely to bias my results and therefore a normal logistic regression is t he best fit to test my research model.
4.2 Descriptive statistics
4.3.1 Dependent variable companyinnovation
The dependent variable studied in this research is companyinnovation. The survey contains four questions on company innovation that are all focused on a different category of innovation: innovation in marketing methods/communication to the public, innovation of product(s) or service(s), process innovation (either for producing goods or supplying services) and innovation to the organization as a whole. This research follows previous studies like Grande, Macías & Pérez (2020) and Muñoz-de-Bustillo, Grande & Fernández-Macías (2017) by studying these innovation categories based on the same survey questions. The variable companyinnovation consists of four categories which are all represented in separate variables:
CI_marketing is constructed from the survey question ‘Since the beginning of 2010, has this establishment introduced any new or significantly improved marketing methods/ methods of communicating your activities to the public?’. CI_productservice is based on practically the same question but it asks whether the establishment has introduced any new or significantly changed products or services (either internally or externally). CI_process comes from the question asking whether the establishment has introduced any new or significantly changed
processes, either for producing goods or supplying services. CI_organizational is based on the question whether the establishment has introduced any organizational change. This type of questioning on organizational innovation is in line with the Oslo Manual, “the foremost international source of guidelines for the collection and use of data on innovation activities in the industry” (OECD, 2005). All four innovation categories are represented in binary
variables; respondents could either fill in yes or no. The four categories are taken together and constructed in an index variable companyinnovation, that describes a composite score for innovation overall. companyinnovation takes on a value between 0-4, where 0 means that the organization has not undergone any sort of innovation, if it takes on a value of 1 at least one of the innovation forms has been implemented, 2 means at least two innovation forms and so forth. No distinction is made between which innovation category is introduced, as they are all important. The most common form of innovation is product/service innovation (introduced in 49% of the organizations), but process and overall organizational innovation follow closely (46%), and finally marketing innovation (40%) is the least introduced. On average,
organizations in the sample have introduced almost two out of the four innovation categories (see table I).
Figure V below shows the percentage of respondent organizations that have indicated they have innovated in any of the four ways, between 2010-2013. It is noticeable that quite some firms have introduced new products, processes, marketing methods or have undergone a general organizational change. Product innovation occurred on average at 46% of the
respondent firms, process innovation at 43%, 42% introduced overall organizational change and 39% improved their marketing methods.
Figure V: Introduction of new or improved products, processes a nd ma rketing methods, a nd orga niza tiona l cha nge, by esta blishment size (%), source: Eurofound (2015).
4.3.2 Independent variable employeeinvolvement
The independent variable studied is employee involvement, which is measured in line with Prouska, Psychogios & Wilkinson (2018). This study examines three different employee involvement practices; regular meetings between employees and managers, information flows and transparency, and suggestion schemes. The question asked which of the following
practices are used in this establishment to involve employees in how work is organized. Three different sub-questions represent the three practices of employee involvement analyzed.
These are; ‘regular meetings between employees and immediate manager’, ‘dissemination of information through newsletters, website, notice boards, email, etc.’, and ‘suggestion schemes (the collection of ideas and suggestions from the employees, voluntary and at any time, traditionally by means of a ‘suggestion box’)’. These three employee involvement practices are respectively represented in the variables EI_meetings, EI_information, and EI_suggestion.
They are all binary variables (respondents either answered yes or no to the question whether these practices are in place).
Figure VI provides insight into the differences in employee involvement instruments that have been implemented. Regular meetings between employees and their immediate manager are by far the most commonly used practice, it is implemented in 85% of the firms.
Approximately 66% of the establishments involve employees by disseminating information through various channels. Finally, the last involvement practice examined in this study is the use of suggestion schemes, which is adopted by 41% of the respondent firms.
Figure VI: Instruments for employee pa rticipa tion, source: Eurof ound (2015).
The three different employee involvement practice variables are taken together and constructed into an index variable named employeeinvolvement, which depicts an overall assessment of the implementation of employee involvement in general. It takes on a value between 0 (no employee involvement practices are implemented) up until 3 (all three
employee involvement practices are implemented). The values 1, 2, and 3 respectively mean either one, two or three involvement practices are in place. No distinction is made between the practice that has been introduced, as they are all (equally) important. From Table I it can be observed that the most used employee involvement practice is regulating meet ings between managers and employees. This practice is implemented in 90% of the respondent
organizations. After that, the dissemination of information happens in almost 80% of the organizations, and finally suggestion schemes is the least used method and is found in approximately 51% of the cases. On average, more than two practices are implemented.
4.3.3 Moderator variable workautonomy
The moderator variable studied in this research is workautonomy. It is based on the question
‘If you think about the tasks to be performed by the teams: Do the team members decide among themselves by whom the tasks are to be performed or is there usually a superior distributing the tasks within the team?’, based on Grande, Macías & Pérez (2020) and Russo
& van Houten (2020). It regards the overall workplace autonomy from the manager’s
perspective, and it is a binary variable (team members decide among themselves =1, tasks are distributed by a superior =2). Its average value is 0.25, which means that in 25% of the organizations in the sample, team members can decide among themselves how tasks are distributed instead of a superior doing this. To test this moderation model, an interaction term is created between workautonomy and employeeinvolvement; autonomy_involvement.
4.3.4 Control variables
This study includes four control variables.
First, whether employees work part-time or full-time, i.e., the number of hours they work, should be controlled for, as for example Frosch (2011) and Sauermann & Cohen (2010) find that this influences the level of innovation. The parttime variable is measured based on the question ‘Could you please tell me for this establishment, the number or percentage of employees, who work part-time, that is less than the usual full-time arrangement’. Possible responses are; none at all, less than 20%, 20%-39%, 40%-59%, 60%-79%, 80%-99%, all, don’t know.
Second and third, the level of education and gender of employees have an effect on the individual level of creativity (Jaskyte & Kisieliene, 2006), which is related to innovation (Anderson, Potočnik & Zhou, 2014). Someone’s education level reflects the knowledge and skills he/she possesses and could therefore influence the level of innovation contributed to the
company (Cheung, Gong, Wang, Zhou, & Shi, 2016). education is measured by asking the respondent what percentage of employees have a university degree. gender is based on an estimation of what percentage of employees are female. For both variables, possible responses include: none at all, less than 20%, 20%-39%, 40%-59%, 60%-79%, 80%-99%, all, don’t know.
Fourth, this study controls for company size because it influences organizational participation (Blumentritt, Kickul & Gundry, 2005) and larger firms have more resources compared to smaller firms which makes them more likely to implement innovation methods (Liu, Gong, Zhou & Huang, 2017). From figure VII below it can be seen that controlling for the company’s size is crucial, as the level of employee involvement in decision-making differs substantially between small, medium-sized, and larger organizations.
Figure VII: Level of employee involvement in decision -ma king in most importa nt recent cha nge, by esta blishment size (5), source: Eurofound (2015).
The variable companysize is based on the question ‘Approximately how many employees work in the establishment? Please include all employees that are formally based in this establishment, regardless of whether they are physically present or carry out their work outside of the premises. Each employee is counted as one person, not taking into account whether they are working full-time or parttime (= headcount).’ The three categories are; 10- 49, 50-249, and 250+.
The descriptive statistics and correlation table are included in this section, for the purpose of a clear understanding of the findings. The results of the different models will be displayed in various regression output tables below3.
3 Plea se note tha t the pseudo R-squa red is not interpreted a nd mentioned sepa ra tely in the results section, beca use in logistic regression a na lysis it does not represent the proportion of expla ined va ria nce, a nd therefore does not provide a ny useful insights. The F-va lue is not reported a s it is used only for linea r regressions.
Table II shows the regression results from model 1. It can be seen that the coefficient for employee involvement is positive and significant at a 1% level. This suggests that the more employees are involved in organizational decision-making through either one of the involvement practices, the higher the probability that there is innovation at the company level.
This effect stays significant while adding all control variables and the fixed effects, therefore H1 is supported. The control variables are all significant.
From Table III it can be seen that conform expectations, all three forms of employee involvement practices; regular meetings, dissemination of information, and suggestion schemes, increase the probability of a high level of company innovation. All coefficients are highly significant at a 1% level. Hypotheses H1a, H1b, and H1c are supported. The
coefficient on information dissemination has the highest positive value. Because causality cannot be proven, it cannot be stated explicitly that information dissemination is the most effective involvement practice in order to achieve high innovative output, though it seems that the results indicate this. All controls are significant as well and the results remain strong when industry and country fixed effects are added.
Table IV shows the regression results from model 3 in which the second hypothesis is tested. To determine the moderation effect of workplace autonomy on the relationship
between employee involvement and company innovation, workplace autonomy as well as the interaction term between workplace autonomy and employee involvement are added as independent variables to the model. Hypothesis 2 expects that autonomy strengthens the positive relationship between involvement and innovation.
The coefficient on employee involvement (column 1) is significant at a 1% level. The coefficient on workplace autonomy (column 2) is also significant but at a 5% level. It is noticeable that workplace autonomy is not strong throughout the model as it becomes insignificant as soon as the interaction term between autonomy and involvement, as well as the control variables, are added. The interaction term that tests the moderation effect is insignificant, therefore no conclusions can be drawn regarding whether workplace autonomy influences (strengthens or weakens) the relationship between employee involvement and company innovation in any way. Hypothesis 2 is rejected. Again, all control variables added are significant.
For the purpose of exploratory reasons, it is analyzed whether there are separate
employee involvement practices. The following models are tested4; model 4 is an extension of model 1 to examine whether the effects of employee involvement are different for the various categories of company innovation. Model 5 tests the moderation model again, but now with the specific involvement practices.
The tests for model 4 are shown in Table V and examine whether employee
involvement in general has a different effect on the four categories of innovation studied in this research. Column 1 until 4 represent the four different innovation categories
(product/service, marketing, process, and organizational innovation). Columns 1 until 8 represent the same innovation categories respectively but with fixed effects included. All coefficients on employee involvement are again positive and highly significant (at a 1%
level), also when adding the country and industry fixed effects. The coefficient of employee involvement on organizational innovation (columns 4 and 8) has the highest value. It could be cautiously suggested that involving employees in organizational d ecision-making might be
most beneficial when stimulation of overall company innovation is pursued.
Finally, model 5 tests the moderation model with the three employee involvement practices separately, as shown in Table VI above. It is noticeable that all three practices are highly significant throughout the model. The coefficients on involvement through regular meetings and information dissemination are significantly higher compared to the overall involvement variable in table IV. This might suggest that these two employee involvement practices have the highest positive influence on company innovation, compared to suggestion schemes. Workplace autonomy is only significant before adding any controls, so it does not provide any useful insights. The moderator is insignificant throughout. Therefore, no conclusions can be drawn regarding whether workplace autonomy affects the relationship between employee involvement and company innovation.
6. Discussion and conclusion 6.1 Summary of main findings
This paper studied three models. Through the first model, the effect of overall employee involvement on the probability of company innovation was examined. It is found that
employee involvement has a positive effect on company innovation. In the second model the effect of three different employee involvement practices on company innovation was
analyzed. All three practices i.e., regular meetings between employees and their superior, suggestion schemes, and the dissemination of information, do contribute to companywide innovation. The third model that has been studied analyzed the moderation effect of workplace autonomy on the relationship between employee involvement and company innovation. The moderation coefficient came out to be insignificant, so nothing can be concluded about the effect of workplace autonomy as a moderator on the relation between involvement and innovation. Two extra models have been studied for exploratory reasons.
Model four analyzed the effect of employee involvement on different categories of company innovation. The coefficient for organizational innovation has the greatest positive value compared to the other innovation forms. However, it cannot be concluded that involvement has the largest effect on that innovation category. This is the case because causality cannot be proven due to selection bias and the cross-sectional nature of the dataset. The fifth and final model depicted the different involvement practices within the moderation model. Again, no evidence for the moderator variable affecting the positive involvement-innovation
relationship is found.
The first model results confirm and enrich, with new and more recent data, findings in existing literature. In line with studies from Datta, Guthrie & Wright (2005); Hayton (2003);
Rangus & Slavec (2017) and Andries & Czarnitzki (2014), it is found that employee involvement and innovation are positively related. This suggests that involvement is still a key factor in improving company’s innovativeness.
The second model is in line with the expectations and in conformity with the study from Zhong (2018), who finds that information provision in the form of transparency, increases a company’s innovative efficiency and effort. The coefficient on suggestion
schemes is low compared to the coefficients of the other two involvement practices. Although nothing should be concluded from the value of the coefficient as causality is not proven, this is noticeable. This might be explained by the fact that whether employees contribute to handing in ideas through suggestion schemes depends on the culture of the organization as well as the employees’ individual characteristics (Jabeen, Mehmood & Mehrajunnisa, 2020).
Merely introducing such a suggestion scheme does not automatically lead to more
involvement, and therefore might stimulate innovation to a lesser extent. Another interesting observation of the second model is the applicability of the results in the current timeframe, due to the corona crisis and an ever-increasing availability of information. The corona crisis has forced an increasing number of employees to work remotely, lowering the barrier for a virtual relationship between employee and employer. The combination of increased
experience with virtual relationships for much more employees and the current online systems that facilitate suggestion schemes, as also discussed in section 2.1.1, might make suggestion schemes a more important factor of influence. Moreover, employee involvement in the form of regular meetings between employees and their managers, is also encouraged by the current corona circumstances. Due to the online nature of the meetings and the familiarization of
virtual relationships, no physical and logistical planning is needed, making meetings easier to take place. The ever-increasing availability of information introduces new phenomena like disinformation, fake news and alternative facts, referred to as ‘misinformation’. This might lead to employees, knowingly or unknowingly, bringing misinformation as ideas and suggestions to the organization. This might call for a scrutiny check; a fact checking entity within an organization that regulates the information and its use.
The third model shows that there is no evidence found for workplace autonomy to influence the relationship between involving employees and company innovation. This finding is in line with the results of a recent study of Echebiri (2020), who finds that the moderating role of perceived job autonomy on the relationship between self-leadership and employee driven innovation does not exist. Although this study is not fully comparable, the results might be interpreted the same way because the studied concepts are close and partly overlapping. Therefore, one might conclude that workplace autonomy is not the most relevant factor when studying the relationship between involvement and innovation.
The fourth model extends model 1, by distinguishing between the four innovation categories in the analysis. This does not result in substantial additional findings, other than that the expected positive relationship between employee involvement and company innovation is confirmed. However, some other observations in this model are noteworthy.
Four different innovation categories are analyzed in table V. The coefficient of two of those categories, process and organizational innovation (column 3 and 4), decreases when fixed effects are added (column 7 and 8). It means that part of the effect as measured in columns 3 and 4 is explained by country and industry differences. This suggests that the effect of employee involvement on process/organizational innovation is dependent on country and/or industry differences. However, the coefficient values of the effect of employee involvement on product/service and marketing innovation (column 1 and 2) increase once fixed effects are
added (columns 5 and 6). This might be explained by country/industry differences initially having a decreasing impact on the coefficients of product/service and marketing innovation in column 1 and 2. When fixed effects are added, this decreasing impact is eliminated as the fixed effects phase out these differences and therefore the coefficient of product/service and marketing innovation increases. I believe these effects are related to the type of innovation being examined. Process and organizational innovation are more technological and skill- based and rely on country differences like culture, attitude, ambition, and education.
Marketing and product/service innovation are more customer-based and are therefore more global uniform due to a global marketplace.
The fifth model gives the same results as founded in model 3 despite studying the three distinct involvement practices. Intuitively, this was not according to my expectations.
Autonomy within a job, as well as feeling more involved in organizational decision-making practices, often tends to stimulate employees’ feelings of engagement and commitment towards the company. Subsequently, commitment increases the effort put into extra-role activities, which in turn enhances innovative output. Furthermore, because workplace autonomy becomes insignificant once industry and country fixed effects are added to the model, the effect is mainly explained by country and industry differences. The cultural differences between the countries and industries on how autonomy in the workplace is perceived and executed might explain this observation. Despite the moderator being insignificant, this does not mean that workplace conditions do not affect the relationship between involvement practices and company innovation. Even more so, other workplace conditions should be studied as well, as some probably do influence this relationship, and are therefore crucial in providing insights into the best implementation methods of involvement practices.
This research has seven main limitations. First, the European Company survey 2013 was conducted when Europe was in the process of recovery from the financial crisis. This might have influenced establishments in the way they have filled in the survey, or the way their company was performing at the time. All results should therefore be interpreted while having this in mind (Eurofound, 2015). Second, employees’ age should also be controlled for, as it influences innovation outcomes (Frosch, 2011; Sauermann & Cohen, 2010), however this variable was not included in the dataset and is therefore not taken into account. Third, this study contains subjectivity. Data derived from surveys is always subjective as it contains self - reported measures (Kahnweiler & Thompson, 2000). Respondents might not answer
truthfully, or they don’t spend enough time to think about the questions and come up with a considerate answer. Moreover, as all variables are answered by managers, one could argue how accurate measures are. For example, employee involvement is indicated by the manager.
It could be the case that he/she believes employees are involved to a great extent, whereas employees themselves believe this to a lesser extent. Fourth, the interviews are conducted by phone which means that visual expressions or signals are not taken into account (Garbett &
McCormack, 2001). This could have caused misunderstandings between the interviewer and interviewee or result in or misinterpretations of certain questions. Fifth, because a cross- sectional dataset is used for this research, causality cannot be proven (Tesluk, Vance, Mathieu, 1999). It could be the case that when employee involvement and innovation are measured over the years, results are different. As innovation is difficult to measure in a single moment and is more likely to be a process that takes time, this might be the case in this study.
Both company innovation, as well as the employee involvement practices, are indicated as dummy variables, therefore nothing can be concluded regarding the extent or intensity of these concepts (Grande, Macías, & Pérez, 2020), which limits the practical implications that
can be derived from this research. Sixth, Bertrand & Mullainathan (2001) find that the answer given to certain questions highly depends on the word choice of the interviewer or the order in which the questions are asked. Finally, in the fourth model, it should be taken into account that the definition of ‘organizational innovation’ is rather vague. When filling in the survey, managers might have classified innovation within their establishment as ‘organizational innovation’, while others would put the same innovation form under product/service
innovation, or nowhere at all. Because these perceptions regarding the understanding of the various innovation categories might differ, results could be biased. It should be taken into consideration that all the above-mentioned limitations could cause biases.
6.4 Future research opportunities
Future research in this area is strongly recommended as the line between employees and their supervisors might fade in the future of work. Possibilities for future studies include examining other workplace characteristics as a potential moderator on the relationship between
involvement and company innovation. Furthermore, it would be interesting to take a better look at comparing various involvement practices. Understanding which practice is most beneficial for particular types of organization, and to what extent they should be incorporated, would increase both the organization’s efficiency as well as its performance. Finally, a
country comparison could be conducted, to deepen knowledge on differences in the effectiveness of involvement practices between countries, and whether they are driven by culture or other aspects.