Master Thesis
''More engaged and innovative behavior at work? An empirical analysis of the relationship between dispositional mindfulness and innovative work behavior through
different motivational influences on the job.''
by Ben Fleer S2293447 Bankastraat 38 9715CD Groningen f.b.fleer@student.rug.nl University of Groningen Faculty Economics & Business
22nd of January 2016 Word count: 12.785
Abstract
Both work engagement and innovative work behavior are widely studied topics. However, not all antecedents and their benefits to enhance these concepts are fully understood. This is where this study realizes an analysis of the more recent concepts of dispositional mindfulness and psychological capital and investigate what kind of effect they have on engaged and innovative behavior. Dispositional mindfulness is build out of Non-reacting to internal experiences, acting with awareness, describing or labeling with words, observing feelings and thoughts and non-judging to external experiences. This was tested using the Five Facet Mindfulness Questionnaire by Baer et al. (2006). Psychological capital is measured through items of the PsyCap questionnaire by Luthans et al. (2007). It consists out of dimensions of hope, optimism, self-efficacy and resiliency. Work engagement is build out of vigor, dedication and absorption and was measured with the UWES-scale (Schaufeli et al., 2006). Innovative work behavior consists out of idea generation, -championing and -implementation and was measured through the IWB-scale by De Jong & Den Hartog (2010). Data was drawn using these measurements, where the sample consisted out of Dutch and English workers which were well dispersed in age. Results show that dispositional mindfulness has a positive effect on engaged and innovative behavior where psychological capital only has a positive effect on work engagement and a small negative effect on the cognitive side of innovative behavior. At the end of the study, managerial implications and further research directions are discussed.
Introduction
Do you remember the last time when your supervisor or a speaker you visited fascinated you so much by explaining his or her story passionately and energetically? Do you recall the occasion you missed the last train connection due to delay and the railway service officers were doing their utmost to help you out getting home? There's a substantial chance that the people you met in these occasions were engaged in their work. According to a survey of 656 chief executive officers (CEO's) from all over the world, Nowadays, one of the most important challenges for management is enhancing engagement in the workplace (Wah, 1999 in Attridge, 2009). Different important entities have focused on this issue, such as the society for human resources management (SRHM) (Clark, 2008) and executive consultant organizations like the Conference Board (Attridge,2009). To adress the issue, researchers have introduced the concept of work engagement (WE), integrating employee engagement and psychological wellbeing (Robertson & Cooper, 2010; Michel et al., 2014). Research started delving into this, because in many companies individual's minds are not aligned, easily distracted from work and achieving poor performances throughout.
Trying to overcome these problems of motivational stagnation and misalignment, engagement proved to be a fruitful concept and research moved on to understand its antecedents. Among them recent literature has introduced dispositional mindfulness and psychological capital (Leroy et al., 2013; Malinowski & Lim, 2015; Luthans et al., 2007).
We already know different factors that enhance work engagement (WE) which are meaningfulness, safety and availability (Kahn, 1990); job resources like social support from colleagues, performance feedback, skill variety, autonomy and learning opportunities (Bakker & Demerouti, 2008; Schaufeli, Bakker & Van Rhenen, 2009); and personal resources such as self-efficacy, organizational-based self-esteem and optimism (Xanthapoulou et al., 2009a, 2009b in Bakker et al., 2011). Note that a lot of the personal resources are also to be found in the mechanisms of psychological capital (Luthans et al., 2007). This study tries to add dispositional mindfulness to the engagement model and find empirical evidence for these relationships. Light will be shed on the concept of psychological capital, where both concepts will be analyzed for impacts on IWB.
In short, this study handles the concepts of WE and IWB as outcomes, which are subjected to quantitative analysis to uncover more evidence about dispositional mindfulness and psychological capital and their proposed influences on the former concepts. Several recent studies tried to address these relationships separately already (Leroy et al., 2013; Malinowski & Lim, 2015 & De Spiegelaere et al., 2016). This study tries to combine empirical evidence for IWB and WE, while also including dispositional mindfulness and psychological capital, along with some organizational factors of preparedness.
Research Questions
Concerning the goals of this study, three research questions are formulated:
- What is the relationship between dimensions of dispositional mindfulness and innovative work behavior?
- What is the relationship between dimensions of psychological capital and innovative work behavior?
- Does the concept of work engagement mediate between the relationships of psychological capital, dispositional mindfulness and innovative work behavior?
- What influence do the levels of job autonomy and top management support have on the relationship between dispositional mindfulness, work engagement and innovative work behavior?
Literature Review Innovative Work Behavior
resources and information. 'Good idea generators' see problems or performance gaps from a different angle. 'Kaleidoscopic thinking' is what Kanter (2000) calls it, as it involves reorganizing existing pieces into a new nicely looking arrangement. Idea championing becomes relevant when the idea has been generated. As ideas not always match with the current organizational routine, it is very important to find support and build coalitions by expressing enthusiasm and confidence about the future success of the innovation. All the while being persistent and finding the right people (De Jong & Den Hartog, 2010). Lastly, ideas need to be implemented. To implement ideas one needs adequate effort and a result-oriented attitude (De Jong & Den Hartog, 2010; Reuvers et al., 2008). An employee can be involved in all these behaviors at the same time, because innovation is often characterized by discontinuous activities. This means that employees arrange the plan for the innovation, although it always turns out different and more chaotic, allowing them to swap behaviors (Janssen, 2000). Furthermore, Kanter (2000) stated that fault-finding behaviors matter. Testing and modifying the new products, services and processes.
Work Engagement
The literature about WE is well developed and has different approaches and corresponding definitions and measures. The most favored approaches are (Shuck 2011):
- Kahn's Need-Satisfying Approach (1990);
- Maslach et al.'s Burnout-Antitheses Approach (2001);
- Harter et al.'s Satisfaction-Engagement Approach (2002) and; - Sak's Multidimensional Approach (2006).
Kahn's (1990) need-satisfying approach is the first theoretical engagement approach applied to the work field. Where the term ''engagement'' was specifically used to describe the involvement of the employee towards various tasks of their work (Shuck et al., 2011). Kahn cast a wide scholarly inquiry and studied previously well-researched theories on the individual's and organizational level such as job stress theory, social identity theory, job design and emerging literature on emotion in the workplace (Thoits, 1991; Ashforth & Mael, 1989; Hackman & Oldham, 1980; Hochshield, 1979 in Shuck et al., 2011). He went on defining engagement as: “the simultaneous employment and expression of a person’s ‘preferred self’ in task behaviors that promote connections to work and to others, personal presence, and active full role performances” (Kahn, 1990; P. 700). As suggestion to his work, Kahn argued that employees could be physically, emotionally and cognitively engaged (Kim, Shin, Swanger, 2009; Shuck et al., 2011). He provided a conceptual foundation for the issue, but he hasn't operationalized the definition.
study. The burnout-antithesis approach has had the most scrutiny. The items measured in this approach are believed to have the most thorough content. Furthermore, it is the most convenient for researchers to measure via the Utrecht Work Engagement Scale (UWES) and also most popular (Schaufeli et al., 2006).
Satisfaction-engagement approach. Other researchers argued for a broader view on engagement as a result of the growing interest in the positive psychology literature. Researchers have taken interest in integrating concepts like psychological capital in the concept. While defining engagement as an ''individual’s involvement and satisfaction with as well as enthusiasm for work'' (Harter et al., 2002, p. 417), they used the Gallup Work Audit to suggest that engagement has a positive influence on customer satisfaction, productivity and profitability. This Survey of twelve questions mostly covers the same ground as the UWES, but targets more on the concepts of supervisory support, job autonomy and emotional aspects of the relationships between workers. This makes the measurement a bit chaotic and therefore we not use it, but nonetheless, it gave us inspiration to integrate 'psychological capital', 'job autonomy' and 'top management support' in our model.
Multidimensional approach. Researchers that contribute to this approach are trying to
summarize the three other approaches while saying that employees can be engaged to the job level and the organizational level. They further state, following Kahn (1990), that employees can be cognitively, emotionally and physically engaged.
commitment, job involvement (Hallberg & Schaufeli, 2006) and job satisfaction (Song et al., 2012 in De Clercq et al., 2014). The concept of work engagement is proved by literature to be a valuable and reliable construct (Schaufeli et al., 2002; Schaufeli et al., 2006; Halberg & Schaufeli, 2006; Halbesleben et al., 2009).
According to various studies, routine workplace innovations are crucial for a company's survival and value (Janssen, 2000). WE is not a momentary mood and isn't focused directly towards an individual, object or a behavior. It has a more continuous character (Bakker & Demerouti, 2008). Also WE is related to the job itself, the dimension 'absorption' isn't the same as IWB, because it is the cognitive motivational element towards the job, whereas IWB demonstrates outcomes of absorptive capacities and encloses a more holistic view.
Work Engagement and innovative work behavior
A lot of research has been conducted regarding antecedents of IWB. However, this research was focusing on intrinsic motivation as a mediating variable instead of WE (Yuan & Woodman, 2010). To give insight on the concept of WE and to build a foundation for a few arguments on its relationship with IWB we apply the variable. Intrinsic motivation is comparable to WE, yet they are not the same. Intrinsic motivation is the motivation which is nestled in the root of the task (Ryan & Deci, 2000). So it is not the extrinsic motivation that comes from, for instance, financial rewards when completing the task, rather it comes from what the employee feels when doing the task (e.g. purpose). WE is contradictory towards intrinsic motivation as it is not a driver for employee engagement, it only measures the degrees of vigor, dedication and absorption experienced by a worker (Schaufeli et al., 2006), without singling out the different sources of WE. In practice these definitions are quite the same (Mauno et al., 2007). This means intrinsic motivation has a lot of overlap with the dedication and absorption dimensions of WE. Researchers found that intrinsic motivation for the task could possibly effect individual's creativity (Amabile, 1996 in Yuan & Woodman, 2010), which is needed for generating ideas and being innovative (Janssen, 2000). This would mean being more dedicated and immersed in your job would account for more innovative behavior, we ought to test these relationships.
managing job demands better (Bakker & Xanthopoulou, 2013). The absorption and dedication dimensions could account for more idea- generating and championing behavior, because an individual that has a higher intrinsic motivational sentiment towards their job will be more immersed and dedicated to do the job. Being actively busy with the job means that more time is spent on the job which means more experience and adding-up knowledge to improve the organizational settings to facilitate this kind of behavior better (De Spiegelaere et al., 2014). We believe that the 'vigor' dimension, which is the human physical energy felt in the job, could account for more stepping-up and taking the initiatives in the organization. The 'absorption' and 'dedication' dimensions are believed to hold more impact on the idea generation and championing (promotion) dimensions of IWB, as these cover the cognitive and behavioral aspects. As a result of these arguments, we hypothesize that:
H1: Work Engagement positively influences innovative behavior.
Dispositional Mindfulness
Good et al., 2015; Malinowski & Lim, 2015; Schultz et al., 2015). This is a rather broad chunk of information to analyze, so researchers came up with a categorization.
The first category is 'non-reacting', which encompasses the ability of an individual to not react to stimuli leaded by the emotions they have at that time, rather to react responsibly when the individual has weighted all reasons and consequences for the different choices that can be made. The second category is 'observing' which refers to observing own feelings, thoughts, perceptions and sensations. This requires the individual to have some know-how about meditation. The third category is 'acting aware', which is acting with awareness, being in the present moment and not distracted by distressing thoughts about the past or future. The fourth category is 'describing' which is the ability of the individual to put their opinions, beliefs, feelings and sensations to words. Lastly, the fifth category is 'non-judging', which is the ability of an individual to not judge him- or herself on own experiences and see them as part of the ride.
Dispositional mindfulness and innovative work behavior
mistakes can be made, because it is normal in the ongoing individual's and organizational experience. By regulating these negative thoughts or images and rather talking about them in an analytical way, one will solve (mental) obstructions faster improving innovative work behavior (Baer et al., 2006; De Spiegelaere et al., 2014).
Other discovered work outcomes of dispositional mindfulness are higher ethical and pro-social behavior and lower deviance (Reb, Narayanan, and Ho, 2015 in Good et al., 2015). These higher ethical and prosocial behaviors have the ability to move a worker to be innovative, because through these behaviors the direct environment of the individual will be approaching more positively and most likely motivate the individual. Through these positive loops of getting a more and more balanced self and organization, individual's positive affect tends to increase (happy, energetic emotions), enabling them to be even more in sync with their jobs while increasing their engagement (Miner & Glomb, 2010; Malinowski & Lim, 2015). We argue that through increased work engagement (more energy, more dedication and more immersion for the job) workers tend to be more up-to-date with their job acquiring in-depth knowledge of their tasks and roles, which could make them more easily think of taking chances to implement new perspectives or smoothen the edges of current work routines and behaviors.
Thus we hypothesize;
H2a: Dispositional mindfulness has a positive influence on innovative behavior
Dispositional mindfulness and work engagement
To build more relevance for this study we analyzed more articles; Bakker (2011) made a comprehensive model of work engagement (WE). His model is about the interaction of job resources and personal resources on WE. These definitions hold all kinds of different characteristics. For instance, job resources include support from top management, job autonomy, feedback from peers and the amount of time available (Bakker & Demerouti, 2008). While personal resources reflect to proactive and reflective behavior and being self-efficient (Mastenbroek et al., 2014). Bakker goes on with arguing that engaged workers' psychological connections to their work and surroundings is of great importance for the organization's competitiveness. We want to build on this argument, by researching through what mechanisms dispositional mindfulness can help strengthen these psychological connections to increase work engagement. This is where our study scrutinizes the role of mindfulness and psychological capital on work engagement to see if more mindful employees are rather to be more entirely engaged in their work (building on Robertson & Cooper, 2010 and Malinowski & Lim, 2015), the healthy way (e.g. no workaholism).
Opening horizons regarding the antecedents that move an individual to be more engaged in their work and analyzing if these antecedents have a direct and/or indirect influence (via WE) on innovative work behavior. Via factor and regression analyses, this study tries to unravel more benefits for building a healthy organizational entity which works well in its dynamic environment, focusing on the concept of dispositional mindfulness in the workplace (Good et al., 2015) . Hence, we conduct a second and third hypothesis:
H2b: Dispositional mindfulness has a positive influence on Work Engagement.
H3: Work engagement mediates the relationship between dispositional mindfulness and innovative behavior.
To our knowledge, this is the first study that tries to find empirical evidence for the interaction between these factors. To bring clarity to the many articles on the different subjects.
The influence of psychological capital
engagement approach on work engagement we described earlier. Those researchers developed a different method to analyze WE, which includes psychological capital dimensions directly into the concept. We add it separately to our model, because we think the 'vigor', 'dedication' and 'absorption' dimensions better measure WE.
To add this concept into our model, we follow Luthans et al. (2007) who defined a new empirical measurement ('PsyCap') to help analyze positive organizational behavior. It consists out of four main sub components: hope, resiliency, optimism and self-efficacy. High levels are achieved when an individual has an optimistic persistent view towards future personal and organizational goals and directs and if necessary re-directs paths towards those goals, while being confident about being able to tackle the challenges of the given tasks and showing adaptability when problems arise. Authors have already displayed that psychological capital has a positive influence on job performance (Wright & Cropanzano, 2000; Luthans, 2002; Luthans, 2007). Furthermore, Seligman & Csikszentmihalyi (2014) suggested that positive psychology (which has psychological capital as a component) could help document what work settings back the greatest satisfaction among workers. Avey et al. (2008) stated that when an individual scores well on the components of PsyCap, they will have increased vigor and dedication for their work through the process of positive affect. Positive affect which spans on 2 dimensions, one of activity (from sleepiness to arousal) and one of emotional tone (from misery to pleasure). Increasing psychological capital will help individuals to get from distress and depression to excitement and contentment (Van Katwyk et al., 2000). Researchers analyzed survey data to state that PsyCap predicts WE through the concept of positive affect (Bakker et al., 2011; Good et al., 2015; Malinowski & Lim, 2015). Hence we formulate our hypothesis:
H4a: Psychological capital will have a positive effect on WE.
other behaviors that make the employee a strong organizational asset (De Waal & Pienaar, 2013). This opens up a view to see the concepts as interrelated, -with a chance to identify beneficial spirals in work-wise thinking and doing (e.g. employee is optimistic, flexible and efficient, gets more into his job and ever (re-)collects new (and old) knowledge, therefore feeling responsible to keep on this level and will feel the urge to increase psychological capital again). This is why we include hypothesis 7.
We want to see if aspects of positive psychology in work engagement are important for innovative behavior, to get a more all-understanding view on the relationship between WE and IWB. While we add mindfulness as an antecedent that maybe could explain how to increase these forces and starting the beneficial spirals in work-wise thinking and doing. Furthermore, Malinowski & Lim (2015) stated that through hope and optimism dimensions, concepts like mindfulness have a beneficial effect on work engagement (WE). It makes sense it would be easier for an individual to keep the objectives in mind and generate new solutions to overcome obstacles if one keeps his or her head calm without automatically reacting to distress. We formulate four more hypotheses:
H4b: Psychological capital will have a positive effect on innovative work behavior. H5: Psychological capital will have a positive effect on innovative work behavior via the mediating dimensions of work engagement.
Conceptual model
Figure 1. Conceptual model
Methods Data collection
the internet through Dutch discussion forums. From this list (so the one with 1021 respondents), every 10th person will be selected for sampling. This was done to reduce self-selection bias. Volunteers will have distinct characteristics that are not representative for the whole population (Floyd & Fowler, 2014). The CEO asked everyone of his network list to fill in the survey.
The next sampling frame contains out of data acquired through Amazon's Mechanical Turk (AMT). Studies have conducted research on the value of this web-based data collection resource to conclude that it's a source of high-quality, low-cost data with fast collection times, underscoring the benefits of a more varied demographic (Grysman, 2015). In addition, Paolacci and others (2010) have requested respondents to fill in why they are completing tasks for AMT and found that 61% responded that they do so to earn additional income, whereas 41% mentioned the entertainment value and 32% listed 'killing time'. The most frequent concern expressed by researchers is that an individual may only get paid one or two dollars an hour. They are worried about the accuracy and adequacy of the respondents (e.g. ''are the respondents paying attention?''). Data quality is a big concern for research and researchers tested if the rate of pay compromises the quality of the results. They found that changing the pay for personality surveys from 2 to 10 and 50 cents does not affect the alpha values, they were nearly identical (Buhrmester et al., 2011 in Grysman, 2015). The only thing affected is the amount of time it took for the researcher to get the same amount of respondents. Thus giving this study a chance to also collect responses from the United States, Great Britain, Australia and Canada to see if the responses are similar to those in the Netherlands. 110 HITs were requested (respondents), respondents were paid $0,25 for their trouble. This is quite a high reward on this market for a survey that only takes a few minutes. This to assure a high response rate and respondents taking the survey seriously.
Variables
The questionnaire consisted out of previously validated multi-item scales. Responses on all scales were calculated on their means. Each multi-item scale represented one of the four constructs in the model. In addition, eight control variables were added to account for demographics and extra external influences which are believed to have a notable impact on work engagement and innovative behavior.
The items of the questionnaire needed to be translated for the Dutch participants. We chose to translate two ways, to indicate mistakes that were made in the English to Dutch translation. The Dutch back to English translation is done by a 49 year old lady that's a native English speaker and has learned the Dutch language for over 20 years. Then the questionnaire was reviewed by 10 respondents to identify further unclarities in the translation. Specific steps and modifications can be found in appendices C & D. The original survey items are to be found in appendix B.
Work Engagement
Dispositional Mindfulness
The Five Facet Mindfulness Questionnaire (FFMQ) of Baer et al. (2006) holds a lot of findings for the different mechanisms that drive mindfulness. The first development of the FFMQ brought forth a five-factor hierarchical structure with mindfulness as a hidden variable that underlies the five facets (Baer et al., 2006). This questionnaire is the most detailed questionnaire there is on mindfulness, because it is originated out of different other mindfulness questionnaires (MAAS, FMI, KIMS & CAMS) (Hayes & Feldman 2004; Baer et al., 2004; Buchheld et al., 2001; Brown & Ryan, 2003 in Baer et al., 2006). After exploratory factor analysis, Baer and others found that the 'observing' doesn't significantly load to the overall mindfulness factor. This is only the case when there is uncertainty about respondents being meditators or not (Baer et al., 2006). In this study, we don't control for respondents being in meditative states so this facet is left out. After confirmatory factor analysis, Baer and his assistants left out items that loaded to multiple facets and ultimately stated there are 39 items that load significantly to a facet (non-judging, observing, non-reacting, acting aware or describing) and ultimately to the overall factor of mindfulness (example item: I can easily put my beliefs, opinions and expectations in to words. Part of the dimension 'describing').
Psychological Capital
To integrate aspects of the satisfaction-engagement, we rely on the PsyCap questionnaire. We don't want to use Harter and others' (2002) Gallup Work Audit (GWA), which is the
questionnaire to test engagement within the Harter et al. (2002) approach, because it integrates all kinds of job attributes like having a best friend on the job, autonomy, (top management) support in materials and equipment and other entirely different but broad definitions like expectations, recognition for good work, progress and the ability to learn and grow. We agree that a lot of the antecedents and outcomes of work engagement (WE) are interrelated, but we think splitting up all these constructs (into for instance hope, optimism, top management support, job autonomy) is the better choice to get an all understanding view of the concept.
effect of psychological capital on work engagement (Example item for the optimism
dimension: When things are uncertain for me at work, I usually expect the best) (Malinowski & Lim, 2015).
Innovative work behavior
This concept is measured through a 9-item scale adopted from the study of De Jong & Den Hartog (2010). This scale is a result of many years of empirical fine-tuning (Janssen, 2000; De Jong & Den Hartog, 2010; De Spiegelaere et al., 2016). Items are divided in three categories; Idea Generation, Idea Championing and Idea Implementation. The three
dimesions, as stated before, are the main three elements from which innovative behavior is built up (e.g.: How frequently do you and/or your colleagues wonder how things can be improved? Part of 'idea generation').
Control variables
Education. According to Finegold and others (2002) it's important to control for demographic factors in the sample. We adopt the scale of the authors where 1 is no high school, 2 is a high school diploma, 3 is answered if they had some college, 4 is a college degree, 5 is a masters degree and 6 is a doctoral degree or higher.
Age. Based on a lot of research, difference in age is important (Finegold et al., 2002). We will ask respondents their years of age to account for differences in age groups.
Function. Respondents are to be divided in Front-liners (FL), Supervisors (SV) and CEO's. This way we control for different function dynamics in the company (Keller, 2015).
Tenure. The amount of years in corporation is measured by the question: 'What is the length of your employment in years?' The categories in which respondents can answer are ''1; less than a year'', ''2; between 1 and 11 years'', ''3; 11 to 21 years'' and ''4; over 21 years'' (derived from Meyer & Allen, 1984).
Industry. In this study we control for the industry in which the respondents work. We do this with a standard scale available in the internet. It's interesting to see difference in sectors. Gender. Men and women are different, this is scientifically proven, so a lot of researchers control for gender (Li & Wu, 2011; Hakanen et al., 2006; Janssen, 2000 for instance).
jobs, the amount of failures that are tolerated and if the organization delegates authority and decision-making to lower-level managers and workers. Research suggests that opportunities are best recognized by individuals that have discretion over how to perform their work as well as by those that are encouraged in experimentation (Kuratko, Hornsby & Covin, 2014).
We measure job autonomy with the items of the work discretion (or job autonomy) factor of the Corporate Entrepreneurship Assessment Instrument (CEAI). The instrument is a result of a decade of conceptual development and empirical fine-tuning (Hornsby et al., 2002; Hornsby et al., 2013; Kuratko, Hornsby & Covin, 2014) and it is likely to be a huge source of knowledge creation (Hornsby et al., 2013). Other research agreed with this while stating that a company's continuous effort in corporate entrepreneurship only happens if individuals are permitted to go on with innovative activities while top management has positive perceptions of these activities. The necessary organizational inputs to enhance innovative work behavior, while willing to take risk and being pro-active (Kuratko, Hornsby & Covin, 2014). The CEAI originally has 48 items (Hornsby et al., 2002). After content- and structural validity tests followed by exploratory- and confirmatory factor analysis, Hornsby and others (2013) found that the new resulting approach, which uses 18 items of the instrument, holds more parsimony when examining the four core dimensions of the concept. For this research, only the items on work discretion will be used. There are 7 items left.
Top management support. When employees are learning clear objectives they are much more likely to be engaged (Clark, 2008; Ireland et al., 2009). When managers facilitate this through organizational factors, job satisfaction among workers will increase (Hornsby et al., 2013). Leading them to be more engaged (Shuck et al., 2011; Bakker, 2011). To measure this variable, the corrected CEAI as described above (Hornsby et al., 2013) results in 5 items for top management support.
Analysis
literature, this method suits the EFA and the confirmatory factor analysis better (Joliffe & Morgan, 1992). On the other hand, PCA is better for totally new concepts which are tested in an exploratory way. We make sure the KMO and Barlett's test of sphericity is on and we enabled the scree plot option, this to make sure factor analysis is appropriate for testing the latent constructs in the present study. Next, analysis will be conducted where the Eigenvalues are greater than 1. We first anticipated to rotate the factors using the 'Promax' rotation technique, because we believed the factors aren't going to be orthogonal. In social sciences, it is believed that the factors correlate to certain values, because behaviors are rarely partitioned into clean functioning units that work independently of each other. Because of the expected correlation, orthogonal rotation results could lead to a loss in valuable information. Therefore an oblique rotation method like the 'Promax' rotation technique is better suited, rendering a more accurate and reproducible solution (Osborne & Costello, 2009). The results are interpreted from a table, searching for the optimum amount of factors within one construct to load the variables in the best possible way to the factors. Items that load negatively to factors or don't load at all are left out. We interpreted the loadings with the different criteria for determining the amount of factors that we need for each latent construct in the study and ran the analysis again with the exact amount of factors we needed for each of these. From there, we computed new factors for further regression analysis.
an impact on how engaged an employee tends to be. In model 3 we also include the dimensions of dispositional mindfulness. With the control variables, the independent motivational variables and work engagement, a strong base is built for measuring the impact of the enhanced form of work engagement on innovative behavior. We test if these relationships are significant. We also test if the relationships in the next model (4) are significant, which consists of the dependent variable innovative behavior (the cognitive side) and the control variables. Next in model 5 we keep the same variables as in the fourth model, but we include the psycap and mindfulness variables. In model 6 we regress all the variables of our model on the cognitive factor of innovative behavior and see if the impacts are different and check if the values are still significant. In model 7, 8 and 9, we do the same as in models 4, 5 and 6. The only thing that's different is the dependent variable, which now is the physical component of innovative behavior. The reasons for this distinction will be made clear later on.
Results Preliminary Results
The sample group was sampled out of the next networks: The 120 people the Dutch CEO asked, 59 people answered to his call. The other 30 were the respondents of the friends list on Facebook. Out of the 1021 people, 102 people were selected, from where 30 answered. So in the first sample that's a non-response rate of 50.8% and in the second sample that rate is 70.6%. Also, using Amazon's Mechanical Turk this study requested 110 respondents and got 117 responses. We think that after the assignment-access period, the HIT was still online and looked appealing, that's why those extra 7 people wanted to contribute to this study. We don't reckon this is a problem because all the respondents were selected at random already (people who were online in that week). The total amount of responses is N = 206.
'Psychological Capital' was the only variable in the analysis that had some problems concerning reliability. The last question (which was one on the 'optimism' dimension; I approach my job as 'every cloud has a silver lining') was misinterpreted by many respondents and didn't have a direct Dutch translation. We left this item out of the analysis, restoring the CA to α = 0,740. Items were loaded on to two factors which were identifying the latent constructs 'hope' and 'optimism'.
Control Variables
The sample group consisted out of 130 (63,1%) men and 76 (36,9%) women. 10,2% of respondents finished middle school, 67% finished high school and 22,8% finished university or higher education. The mean age in the sample was 38,9 years old (SD = 12,3). 47,1% of the sample were employees, 35,4% were managers or supervisors and 17,5% were CEO's or in another high position. For tenure: 11,7% worked at their current company for less than a year. For many others this time was longer; 63,1% works from 1 to 10 years on the job, 14,6% is working at their company between 11 and 20 years and 10,7% is longer than 21 years active at their company. This study has also controlled for the different sectors. All the respondents are quite evenly spread out over the sectors. The only two sectors we didn't find respondents in were building, grounds cleaning and maintenance occupations and healthcare support operations. Most responses came from the sector of sales and sales related occupations.
Factor analysis results
Dispositional mindfulness items loaded on to four factors and PsyCap items loaded on to two factors. They explained 67%, 64%, 60% and 67% of the variance respectively.
The following pages will be dedicated to showing how well the items load on the concepts, laying the basis for the amount of factors chosen in the regression analysis.
Confirmatory factor analysis. Innovative work behavior. For this study's dependent variable, some items had difficulties, they loaded on to both factors (Table 1). These items were deleted. We chose for a two-factor loading solution, because the theorized three-factor solution made all the items load into only the first factor. Loading the items on to two factors, this study still makes the distinction between 'thinking about innovation' and 'doing innovation'. This is in line with the ideas of Mumford & Gustafson (1988), but the third dimension added by other authors (Reuvers et al., 2008; De Jong & Den Hartog, 2010) isn't reflected in these results. The factor loadings when discarding item ''4'' and ''5'' (idea generation) and ''2'' (idea implementation) were a bit higher, though not significantly different from table 1.
Table 1. Factor loadings and Cronbach’s Alpha for IWB scale
Cognitive component
Physical component
IWB 1 Idea Generation .624 .196
IWB 2 Idea Generation .668 .160
IWB 3 Idea Generation .735 .373
IWB 4 Idea Generation .522 .569
IWB 5 Idea Generation .560 .440
IWB 1 Idea Championing .262 .776
IWB 2 Idea Championing .241 .796
IWB 1 Idea Implementation .216 .683
IWB 2 Idea Implementation .452 .651
Cronbach’s alpha .768 .871
Kaiser-Meyer-Olkin Measure of Sampling Adequacy = .907 KMO Barlett's test of Sphericity = .000
both factors. We chose to apply a two-factor solution. Besides that, we made a separate measurement variable for work engagement as a single factor solution, to account for the necessity of the different dimensions and to compare regression outcomes.
Table 2. Factor loadings and Cronbach’s Alpha for WE (UWES) scale
Vigor & Dedication (Positive job energy)
Absorption (Job's Ability to improve attention span) 1-Factor loading Work Engagement Vigor 1 .898 .067 .827 Vigor 2 .862 .191 .848 Dedication 1 .868 .198 .862 Dedication 2 .821 .285 .846 Dedication 3 .724 .327 .747 Absorption 1 .618 .508 .712 Absorption 2 .143 .955 .435 Cronbach’s Alpha .917 .615 .899
Kaiser-Meyer-Olkin Measure of Sampling Adequacy = .905 KMO Bartlett's Test of Sphericity = .000
Table 3. Factor loadings and Cronbach’s Alpha for FFMQ-Scale
Non-Reacting Acting Aware Describing Non-Judging
Non-reacting 1 .555 -.061 .131 .052 Non-reacting 2 .499 .178 .107 .072 Non-reacting 3 .518 .218 .031 .209 Non-reacting 4 .750 .072 .126 .080 Non-reacting 5 .659 .053 .133 .128 Non-reacting 6 .596 .214 .134 .120 Non-reacting 7 .573 -.019 .045 -.033 Acting aware 1 .076 .653 .198 .298 Acting aware 2 .042 .692 .142 .221 Acting aware 3 .095 .756 .072 .176 Acting aware 4 .002 .859 .089 .151 Acting aware 5 .114 .687 .166 .105 Acting aware 6 .215 .672 .075 .233 Acting aware 7 .219 .705 .124 .179 Describing 1 .160 .107 .783 .065 Describing 2 .145 .196 .799 .105 Describing 3 -.015 .445 .611 .207 Describing 4 -.037 .516 .603 .198 Describing 5 -.038 .396 .605 .248 Describing 6 .154 -.074 .454 -.026 Describing 7 .226 .035 .703 -.004 Describing 8 .175 .179 .740 .033 Non-judging 1 .137 .296 -.099 .651 Non-judging 2 .003 .162 .084 .714 Non-judging 3 .092 .219 .190 .691 Non-judging 4 .096 .022 -.107 .658 Non-judging 5 .062 .227 .184 .796 Non-judging 6 .090 .277 .120 .764 Non-judging 7 .093 .166 .124 .708 Non-judging 8 .153 .108 .076 .733 Cronbach’s Alpha .811 .909 .897 .909
Kaiser-Meyer-Olkin Measure of Sampling Adequacy = .875 KMO Bartlett's Test of Sphericity = .000
Psychological Capital. Only using two dimensions of psychological capital resulted in some dubious factor loadings. The alpha values are still valid and some items shifted to the other factor. This shifting is due to the fact that the questions (for instance: When things are uncertain for me at work, I usually expect the best) could be interpreted as measuring
optimism instead of hope. The dimensions are closely related to each other, it could be argued that all these items should load on to one factor where overall α = 0.740. This is why we also include psychological capital as single-factor solution next to the factor variables of
Table 4. Factor loadings and Cronbach's Alpha for PsyCap Scale Optimism Hope Psycap Hope 1 .823 -.025 Psycap Hope 2 .816 .262 Psycap Hope 3 .145 .808 Psycap Optimism 1 .727 .196 Psycap Optimism 2 .080 .834 Psycap Optimism 3 .819 .069 Cronbach’s Alpha .821 .603
Kaiser-Meyer-Olkin Measure of Sampling Adequacy = .774 KMO Bartlett's Test of Sphericity = .000
Regression results
All the variables were checked for correlation in the correlation matrix (table 5). The values above the 0.8 level can be explained; the factors hold most of the according items, so it's logical that these correlate highly. Thus, multicollinearity problems aren't a concern in this study.
Table 5. Correlations between scales
Table 6. Overall means and standard deviations
1 2 3 4 5 6 7 8 9 10 11 12 13 14
µ 5.32 4.40 4.87 5.07 4.95 4.13 5.17 4.37 4.90 5.34 5.16 5.26 4.51 3.83
σ 1.17 1.28 .94 1.32 1.13 1.35 1.12 1.43 .99 1.25 1.33 1.19 1.18 1.20
Table 7. Regression Analysis Results
General comments. For our models, all ANOVA significance values were beneath 0.001 and thus significant. Besides, the R-squared values, which indicate the amount of variation explained, all scored moderately high in our analysis. This means that 28% - 62% of the variation can be explained by interpreting these values in the different models.
Other control factors. The other control variables like education, function, tenure and gender don't hold significant affects on our model. The only interesting finding here is a negative influence on the physical side of innovating on gender. This would imply that the women in our sample are less involved in implementation of new innovations than men. Though this is a really small sample, and we further comment that all the variables except these other control variables were ordinal variables, while these were categorical. The only variable that scored a significant effect on each model was the language that respondents chose. We looked into this, and saw that the respondents that followed the Dutch questionnaire scored well above those that chose to fill in the questionnaire in English.
Hypothesis 1. We hypothesized that work engagement dimensions would have a positive influence on innovative behavior. The outcomes for this relationship aren't significant, therefore hypothesis 1 isn't supported. This may have been a result of using the shortened UWES-Scale while we didn't have a substantial amount of respondents.
Hypothesis 2a. This hypothesis tested if dispositional mindfulness dimensions account for a positive influence on innovative behavior. This hypothesis is partly confirmed, where the dimension of 'acting aware' is the most important dimension on both aspects of innovating. The physical component of IWB is also affected by the dimension of 'describing'. Where the dimension of 'non-reacting' holds one dubious significant negative influence in model 8. This dimension hasn't found to be significant in all other models, and the negative influence in the above mentioned model is small. The two dimensions of 'non-reacting' and 'non-judging' are less important in this analysis, though 'acting aware' and 'describing' are important for innovative thinking and doing.
Hypothesis 2b. For this hypothesis we tested if dispositional mindfulness dimensions has a significant influence on work engagement. We can state that only the 'acting aware' and 'describing' dimensions have a direct significant effect on work engagement, therefore this hypothesis is partly confirmed.
Hypothesis 3. This hypothesis tested if work engagement has a mediating influence between dispositional mindfulness and innovative behavior. We need to reject this hypothesis, because work engagement is found to have no effect on innovative behavior in this study.
Hypothesis 4b. This hypothesis holds an interesting finding. We analyzed if psychological capital has an influence on IWB. We earlier anticipated that this was a positive effect. The results indicate this isn't true. For the cognitive dimension of IWB, psychological capital was found to hold a negative effect. The rest of the effects were insignificant.
Hypothesis 5. Hypothesis 5 tested if work engagement mediates the relationship between psychological capital and IWB. This hypothesis also needs to be rejected due to the same reason as hypothesis 1 and 3.
Hypothesis 6. This hypothesis tested for the influence of mindfulness dimensions on psychological capital dimensions preceding innovative behavior. These influences were all found to be significant for p < 0.10. 'Non-reacting' indicated a standardized beta of .301 whereas 'acting aware', 'describing' and 'non-judging' indicated betas of .295, .125 and .141 respectively. These values are indicated in relation to the cognitive component of IWB, where the values of the physical component of IWB were a bit less, but still hold quite the same outcomes. Therefore hypothesis 6 is accepted.
Hypothesis 7. The last hypothesis of this study tested if work engagement precedes psychological capital to account for the beneficial loops in the interaction of the concepts. This hypothesis can be partially confirmed, because the single-factor solutions of both concepts hold strong influences on this relationship. A beta of .977 (p = .079) was found on the cognitive component of innovative behavior and a beta of .915 (p= .093) on the physical component. These are very high values, which maybe is a bit suspicious. Only the single factor solutions hold these values. All in all there may be an influence, yet we believe it's not such a high influence.
Discussion
to the dimensions of 'acting aware' and 'describing'. Individuals that don't let themselves get distracted and can pronounce their opinions, beliefs and feelings into words tend to be more innovative in a physical way. Through having an open stance towards others, daring to speak of figments and not being distracted easily, workers tend to generate and produce more ideas. This could be stimulated by managers with methods like mindfulness training sessions, which could lead to more innovation (Good et al., 2015). This study also found acting with awareness accounts for a small impact on the cognitive side of IWB. To date, this is the first study that empirically analyzed this relationship. Other studies have tried to analyze how to alter behaviors using mindfulness, but not on the spectrum of innovation.
This study failed to prove that psychological capital has an influence on IWB, the only effect we found was a small negative effect on the cognitive side of innovating. Further research could delve into this, arguing that a too bright perception of the future could lead to less thinking about improvements. For the physical side, implementing ideas through systematic phases requires more than being optimistic. There is a substantial amount of literature available on how corporations should organize their human capital assets to acquire continuous success, which structures to employ to allow individuals to develop processes that can be the most successful and to learn from inevitable failures that are part of being innovative (e.g. corporate entrepreneurship) (Corbett et al., 2013).
This study didn't find any significant relationships between WE and IWB, this means that the mediating function of WE isn't proven. Other studies have analyzed that both the concepts can be positively influenced by all kinds of other external factors simultaneously, but none of them have measured the relationship between the two in this order yet. A few authors have shown that an innovative climate accounts for a positive influence on WE (Bakker et al., 2008).
physical side of IWB and not for the cognitive side. This may be due to the fact that managers connect with employees and envisioning them to 'do' innovation, but can't get through yet to the cognitive level. This is where job autonomy scores better. Letting individuals work by themselves makes them more eager to improve their workplace. This is in line with several other studies, that handle these concepts as 'job resources' that account for positive influences on WE and IWB.
Managerial implications
Through teaching mindfulness, individuals will understand their own brain better. This understanding will have the potential to block-out negative stimuli and refrain from negative reaction impulses. If that's mastered, the brain feels happier through more serotonins. This is an atomic substance in the brain which looks like it's a walking cell on a (nerve) line. Going from nerve to nerve, these cells account for the amount of happiness and positivity in the brain. Feeding the brain good thoughts about the future makes more of these cells 'walk'. The march of positivity and happiness. This state of positive being is partly proven to have an influence on the amount of energy that the individual has and the amount of strive this person has towards the job along with how innovative the individual is.
Limitations and further research
Limitations. The sample size of this research consisted out of 206 respondents. This is an acceptable size, though it's not optimal. The sample was collected out of two sample frames, which also scored differently on the survey. We included this in our analysis, but the data collection procedure could have been done with more caution to get a clearer sample of the population. Also, we asked which language respondents wanted to follow, but we didn't control for the real origin of the respondent.
We earlier anticipated that structural equation modeling (SEM) was a better way to analyze the results. We wanted to choose for SEM techniques for two major reasons; the first reason is that it allows for multiple regression equations to test simultaneously. Because this study contains a model that has a multivariate character where (partially) mediated relationships are anticipated, this way of analyzing is preferred to overcome the bias of individual regression estimations to build a path model. The second reason for using SEM is that the expected correlations between the latent constructs are assumed to be high. Regression estimates are further biased by this, as the individual regression techniques assume that the independent variables are uncorrelated. Adding covariance terms in the model, this bias could have been reduced (Monsen & Boss, 2009). Due to the fact that this knowledge was missing along with a program like AMOS, we were unable to conduct analysis this way.
Further research. Some relations tested by this study were insignificant. Though there are still arguments to test these relations, especially WE on IWB. Up until now, all studies to our knowledge have seen work engagement as a dependent variable that is influenced by job resources and job demands. Maybe engaged employees tend to increase their own job demands to make their own direct environment more challenging, in order to do that they may start up new projects, which a display of innovative behavior. Researchers could delve into this relationship and analyze if work engagement can influence innovative behavior this way, or that it only is a dependent variable.
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Appendix A: Table of Contents
1. Abstract 2
2. Introduction 3
3. Research Questions 5
4. Literature Review 5
4.1 Innovative Work Behavior 5
4.2 Work Engagement 7
4.3 Work Engagement and Innovative Work Behavior 9
4.4 Dispositional Mindfulness 10
4.5 Dispositional Mindfulness and Innovative Work Behavior 11
4.6 Dispositional Mindfulness and Work Engagement 12
4.7 The influence of Psychological Capital 14
5. Conceptual Model 17 6. Methods 17 6.1 Data Collection 17 6.2 Variables 19 6.2.1 Work Engagement 19 6.2.2 Dispositional Mindfulness 20 6.2.3 Psychological Capital 20
6.2.4 Innovative Work Behavior 21
6.2.5 Control Variables 21 6.3 Analysis 22 7. Results 24 7.1 Preliminary Results 24 7.2 Control Variables 25 7.3 Factor Analysis 25
7.3.1 Exploratory Factor Analysis 25
7.3.2 Confirmatory Factor Analysis 26
7.4 Regression Results 29
8. Discussion 32
8.1 Managerial implications 34
8.2 Limitations and Further Research 34
8. References 36
Appendix C: Survey Questions
All questions will be conducted using a 5 point scale where respondents can choose from 1 totally disagree, 2 disagree, 3 not sure, 4 agree and 5 totally agree.
TOP MANAGEMENT SUPPORT
People are often encouraged to take calculated risks with ideas around here.
This business unit supports many small and experimental projects realizing that some will undoubtedly fail.
Senior managers encourage innovators to bend rules and rigid procedures in order to keep promising ideas on track.
Those employees who come up with innovative ideas on their own often receive management encouragement for their activities
Money is often available to get new ideas off the ground.
WORK DISCRETION
This organization provides the chance to be creative and try my own methods of doing the job.
This organization provides the freedom to use my own judgment.
This organization provides the chance to do something that makes use of my abilities. I have much autonomy on my job and am left on my own to do my own work.
Innovative Work Behavior
Measured with a 7-point scale where 1 = Never, 2 = Seldom, 3 = Sometimes, 4 = Occasionally, 5 = Quite often, 6 = A lot of the time, 7 = All the time
