GENERATION MANAGEMENT
Setting the right conditions to stimulate knowledge sharing and innovative behavior. A focus on the 50-65 work population within Company X
Master thesis, MSc, specialization Human Resource Management University of Groningen, Faculty of Economics and Business
July – January 2012 ELLEN WITJAS Student number: 1666622
Supervisor – University Drs. M. Fennis-Bregman Supervisor – Field of Study
TABLE OF CONTENTS
ABSTRACT--- 4
INTRODUCTION--- 5
The Ageing Workforce--- 5
Company X--- 5
Knowledge Sharing and Innovative Behavior--- 6
High Job Satisfaction and Positive Attitudes towards HR-Practices--- 6
Research Goals--- 7
CONCEPTUAL FRAMEWORK--- 8
The Ageing Workforce--- 8
Knowledge Sharing Behavior--- 11
Innovative Behavior--- 13
Job Satisfaction--- 15
HR-practices--- 16
Training and Development--- 18
Working Project Based--- 19
Intergenerational Teams and Mentor Relationships--- 19
Research Questions--- 21 METHOD--- 22 Research Design--- 22 Sample--- 22 Measurements--- 23 Personal Information--- 23 Job Satisfaction--- 23 HR-Practices--- 24
Knowledge Sharing Behavior--- 25
Innovative Behavior--- 25
RESULTS--- 26
Reliability and Correlation Analyses--- 26
One-Way Between-Groups ANOVA analyses--- 27
The Three Different Age Groups--- 28
Job Satisfaction and Knowledge Sharing Behavior--- 29
Attitude towards HR-Practices and Knowledge Sharing Behavior--- 31
Job Satisfaction and Innovative Behavior--- 33
Attitude towards HR-Practices and Innovative Behavior--- 35
DISCUSSION--- 38
Research Findings--- 38
Practical Implications--- 40
Research Limitations--- 43
Suggestions for Future Research--- 44
REFERENCES--- 46
APPENDIX--- 50
ABSTRACT
For organizations like Company X innovation is the key to success in order to create competitive advantage. To be innovative, you need to manage the existing as well as creation of new knowledge within the organization very well. Company X’s workforce is ageing and with the retirement of a large population in the coming decade, the risk is prevalent that they take along a significant amount of knowledge and expertise when they leave. I aimed to investigate the current job satisfaction and attitude towards HR-practices to see what can be improved to stimulate knowledge sharing and innovative behavior among the 50-65 workforce of COMPANY X. I conducted an explorative cross-sectional study using web-based questionnaires to gather data. Findings suggest that the variance between groups with low and high scores on knowledge sharing and innovative behavior might be due to intrinsic job satisfaction and a more positive attitude towards HR-practices. COMPANY X might start to focus on the intrinsic job satisfaction of their employees and reconsider their HR-practices, to maximize the potential of employees within this age group. Focus groups composed of employees within the 50-65 work population can help to provide the answers on how this can be done.
INTRODUCTION The Ageing Workforce
The average age at the workforce is increasing due to the greying and hazing of our overall population. Today, the largest segment of the working population has an age between 45 and 55 and the average age will only increase in the coming years (CBS, 2011). Attention towards the ageing workforce and everything that it brings along becomes increasingly important for organizations.
Many companies expect ageing issues in the coming years. When companies care about these issues, the focus is mostly on the short instead of on how to manage ageing in the, nearby, future. Ageing issues are mainly about the crooked building of the workforce, rigidity of the organization, a lack of through flow, motivation and changeability of the older workers and the loss of valuable knowledge (Vergrijzingsmonitor 2010; Ng & Feldman, 2008). The latter is a prevalent risk for the organizations, as a consequence of the retiring workforce; many knowledge and expertise may be lost. This can have an impact on the innovative ability of organizations, which is especially important in research and development industries. Organizations and in this case, Company X needs to take a pro-active role in order to manage its senior workforce in the best possible way.
Company X
Knowledge Sharing and Innovative Behavior
COMPANY X’s business is continuously facing enormous challenges due to global developments, local characteristics and changing environments. To sustain and create competitive advantages, and for organizational success, it is important to foster, develop and use the innovative potential of the employees (Dorenbosch, van Engen and Verhagen, 2005). For an organization to be innovative, it is important to manage the existing as well as creation of new knowledge. As a consequence of innovative behavior and good knowledge management, you can increase overall organizational competiveness and prosper the organizational growth.
High Job Satisfaction and Positive Attitudes towards HR-Practices
Research Goals
The section above appoints issues about the ageing workforce on the one hand and the need to transfer knowledge and to stay innovative given the current demographic changes on the other hand. When COMPANY X does not take proactive actions there will be a risk that a lot of valuable knowledge and expertise will disappear in the coming decade and that innovation will stay behind. The question is how COMPANY X can stimulate knowledge sharing and innovative behavior?
I will conduct an explorative cross-sectional study to investigate job satisfaction and attitude towards HR-practices to see whether and where this can be improved to stimulate knowledge sharing and innovative behavior among the 50-65 workforce of COMPANY X. It will also be investigated if there are differences within age groups in what employees need from their work and HR to facilitate the behavioural aspects. In order to obtain the practical insight and advises for COMPANY X in the end, scientific theoretical models and research findings will be discussed and used.
The introduction and research goals above lead to the following research question.
CONCEPTUAL FRAMEWORK
As the workforce is aging rapidly, it becomes increasingly important to understand and know how age is related to different organizational outcomes and to examine contextual factors that enable older workers to show their competence at work (Kanfer and Ackerman, 2005). There is much literature that illustrates that the level of commitment workers feel towards the job and the organization is closely linked to their attitudes to and behavior within the workplace (Hislop, 2003; Chen and Francesco, 2000). Current research investigates what can be done to create the right conditions in order to stimulate knowledge sharing and innovative behavior.
The sections below will define and discuss the most important concepts that are important to answer the research question. First the issues around the ageing workforce will be discussed, second the concepts of knowledge sharing and innovative behavior and finally I will elaborate on job satisfaction and HR-practices.
The Ageing Workforce
The demographic developments ensure that the ageing workforce issues rise in importance on the HR agenda. However, still few companies in the Netherlands made the link between the developments on the labor market and the preferred composition and building of their current and future workforce. This is threatening, since companies fail to envision the needs and future perspectives of the organization coupled to their main resources, the employees (vergrijzingsmonitor 2010). As you can see in the graphs of the CBS in figure 1, the average age in the workplace is increasing compared to ten years ago, and when you look ten years ahead, the largest part of the workforce will be in or around the age cohort of 50-60 years.
Figure 1
Age distribution in the Netherlands in 2001, 2011 and in 2021 (cbs)
As said before, the CBS expects that by 2020 the majority of the workforce is at an age of 50 years and beyond. The coming years must prove the effects of these demographic developments, though it is important to investigate and anticipate on the effects already. The age distribution within COMPANY X, displayed in figure 2, follows the similar trend as the overall age distribution in the Netherlands, as can be seen in figure 1.
Figure 2
Figure 2 shows how the work population of COMPANY X is currently composed and how it will look like in 2020 when no actions will be taken. The population of senior employees increases extremely and the inflow of younger employees decreases. Younger employees can possibly not fill the gap between the low inflow and high outflow, since there are simply not enough. It is clear that the organization will grow older; these demographic developments bring along the risk of an enormous loss of employees when they retire. The expected outflow of overall qualified workers with a lot of experience and knowledge, can lead to a deficit in the needed qualities for COMPANY X, which endangers their strong position in the market.
To investigate the risks of ageing within COMPANY X and to see how they can overcome some of the challenges, current research focuses on the senior population with an age between 50 and 65 years. There are mainly two reasons to take 50 years as a lower bound. The first is outlined in figure 3 of the CBS, where can be seen that the labor participation starts to decline from the age of 50. The second reason is cause of the baby boom generation; people within this generation are born between 1946 and 1960. The youngest baby boomers reached an age of 50 in 2010. Since this group will be the largest in the total work population, and they are all about to retire in the coming fifteen years, it is important to focus attention on these employees.
Figure 3
Net labor participation according to age and gender (CBS, 2010)
phase may start. After an age of 60 the labor participation lowers again, that is why in this research the participants are grouped in three age cohorts:
• Employees with an age in the cohort of 50 - 54 years • Employees with an age in the cohort of 55 – 59 years • Employees with an age in the cohort of 60 – 65 years
The next section will elaborate on the important role of knowledge sharing behavior in the organization.
Knowledge Sharing Behavior
Previous studies have highlighted the importance of knowledge sharing to create new knowledge and thereby innovation (Kogut and Zander, 1992; Nonaka, Toyama and Nagata 2000; Wu and Cavusgil, 2006, adapted from Camelo-Ordaz, Garcia-Cruz, Sousa-Ginel and Valle-Cabrera, 2011). Knowledge is one of the most important keys to success within organizations, especially within Research and Development organizations.
Yi (2009) used a good definition of knowledge sharing behavior in his article, which will be applied in current research: “knowledge sharing behavior is a set of individual behaviours involving sharing one’s work-related knowledge and expertise with other members within one’s organization, which can contribute to the ultimate effectiveness of the organization” (Yi, 2009: 68). Knowledge sharing behavior in this way is limited to the behavior of knowledge providers, not the behavior of knowledge receivers. Work-related knowledge and expertise refer to the know-how, know-why, experiences, ideas, skills and expertise. The knowledge as mentioned here is defined as the explicit job-related information, implicit skills and experiences necessary to carry out tasks (Yi, 2009).
Yi (2009) developed a valid and reliable measure of knowledge sharing behavior. The measurement of knowledge sharing behavior is a pretty new thing, which means there is no definite measure of it. Yi (2009) divided knowledge sharing behavior in four categories; these classified categories are based on literature and are similar to the four major mechanisms or modes for individuals to share their knowledge in organizations defined by Bartol and Srivastarava (2002). The four categories are (1) written contributions, which refer to behaviours of employees that contribute their ideas, information and expertise through written documentation. (2) Organizational communication, which includes behaviours of sharing knowledge in formal interactions within or across teams or work units. (3) Personal interactions, which refer to knowledge sharing in informal interactions among individuals, by chatting over lunch and helping other employees who approach them. (4) Communities of practice, which refers to behaviours of sharing knowledge within voluntary communities of practice around a topic with common interest in a non-routine and personal way. These categories will also be used to measure knowledge sharing behavior in this research.
knowledge available” (Liu and Liu, 2011: 982). Since knowledge is so valuable for R&D, it is important to know how COMPANY X can stimulate knowledge sharing behavior. Employees within COMPANY X indicate that many knowledge and expertise is and stays with the individuals. There is a lack of shared and thus corporate knowledge, which is worrisome. COMPANY X did create technologies to map and share knowledge electronically. However, Johannessen, Olaisen and Olsen (1999) state that it is an error to think that investment in technologies will automatically also create knowledge sharing. They state that the impetus must be placed on the employees themselves, not on information systems. There is misbelieve that by simply investing in advanced IT equipment, new knowledge will emerge. It is precisely the interaction of humans that creates new knowledge that adds to the corporate knowledge (Yahya and Goh, 2002).
Since the senior work population will retire in the coming years, the present knowledge and expertise about the organization, the processes and especially the scientific research in the lab of the R&D organization needs to be transferred to younger generations. Thereby stimulating knowledge sharing and innovative behavior within this senior population also stays very important to keep up the good work (van den Hooff and Ridder, 2004). The next section will elaborate on the importance of innovative behavior for R&D organizations.
Innovative Behavior
For innovation within the organization, you need innovative behavior of the employees. Jansen, Schonebeek and van Looy (1997) describe that innovative work behavior is a four-stage process that consists of interrelated sets of behavioural activities, namely problem recognition, idea generation, idea promotion and idea realization, showed in figure 4. The first two stages cover the notion of creativity-oriented work behavior followed by the production of novel and useful ideas within the own work context. The last two stages refer to implementation oriented behavior, with also the promotion and championing of novel ideas.
Figure 4
Four stages of innovative work behavior (based on Jansen, Schoonenbeek and van Looy, 1997; Doorenbosch, van Engen and Verhagen, 2005)
Firms engaging in R&D have the goal to create innovations in order to benefit from it eventually. To reach this goal, it is important to share and communicate knowledge as mentioned in the section above. By sharing existing knowledge to others, new combinations of knowledge might exist, which form the basis for emergence of innovation (Olander and Hurmelinaa-Laukkanen, 2010). Innovative capabilities of employees can distinguish the organization from its competitors and can create competitive advantages. Company X is a market leader in the FMCG business and a major innovator in the innovation adoption cycle; the Company has to stay ahead with its overall innovations. Especially for COMPANY X much and good innovations bring along interesting and competitive advantages. Therefore it is beneficial to stimulate innovative behavior, which is one of the most important ingredients of the overall organizational performance.
Job Satisfaction
For many senior employees, knowledge represents an important power resource. This means that it is not straightforward to think that employees voluntary share their knowledge. It can especially be hard for the senior workers to share their knowledge that has been build throughout their career and is a valuable personal resource. It may give them status and power, sharing this knowledge can be perceived as a loss of influence within the organization and can be threatening (Hislop, 2003). In order to share knowledge, COMPANY X must set the right conditions to favour the knowledge sharing and innovative behavior of their senior workforce. Brachos, Kostopulos, Sodersquist, and Prastacos (2007) concluded that when the necessary factors for motivating individuals to share and transfer knowledge are present, innovative behavior also improves.
Job satisfaction has important implications for organizational behavior. Job satisfaction can be seen as the collection of feelings and beliefs that people have about their current job (George and Jones, 2005). Job satisfaction is a key determinant of experiences at work and central in understanding and managing organizational behavior. The direct relation is not tested in literature, though high job satisfaction can be a condition to favour knowledge sharing and innovative behavior of the senior employees. Springer (2011) conducted research in the banking industry and found that by increasing job satisfaction, the job performance could be potentially improved. Though overall the relation between job satisfaction and performance is controversial, some show direct relations, some moderate and some no relation (Springer, 2011). Current study tries to find out which parts of job satisfaction might be increased to improve knowledge sharing and innovative behavior which indirectly determine the performance and competitive advantage of the organization.
satisfaction does change cause of age as well. Job satisfaction shows consistently that work related attitudes are more positive when age increases, which means that senior workers may have a different perspective on work, than younger adults. For senior workers, survival needs, where salary and compensation are important for, become less urgent since they often reached the maximum salaries for their job (Sterns and Miktos, 1995). In their study they also showed that job satisfaction for senior employees was more related to intrinsic or internal rewards. It is important to search for the best way to satisfy the senior employees within their job.
Employees differ in the needs they try to satisfy at work and it is not only correlated to age, personality plays a crucial role in this process as well (Warr, Miles and Platts, 2001). Knowing that job satisfaction can influence organizational behavior and performance, and that it may change when age increases, it is interesting to investigate the situation regarding job satisfaction among the senior workers within COMPANY X. When COMPANY X knows which factors of job satisfaction contribute most to more knowledge sharing and innovative behavior, it can be seen where changes might be made in the work situation to create better conditions. HR-Practices
Over the last two decennia, many research dealing with the resource based theories of the firm, agreed that human resources are an important strategic asset for organizations. It is said that human resource systems and practices within the organization can have a substantial impact on the performance and competitive advantage (Becker and Gerhart, 1996; Delery, 1998; Ferris, Hockwarter, Buckley, Harell-Cock and Frink, 1999, adapted form Kusluvan, 2003). Thereby many studies showed a positive relationship between bundles of HR-practices, organizational performance and organizational outcomes (Becker and Gerhart, 1996; Ferris et al, 1999; Huselid, 1995, adapted from Kusulvan, 2003).
Good organizational performance within R&D organizations depends on knowledge sharing and innovative behavior. As said, sooner or later in the coming decade a large group of senior employees will retire, thereby they will take their valuable knowledge and expertise. To avoid this, COMPANY X can take actions to transfer many knowledge and expertise.
on specific organizational interventions that may help organizations encourage knowledge sharing. Current research will focus on the latter and by organizational interventions current research refers to HR-practices. HR-practices have become recognized as essential for the promotion of knowledge sharing within an organization. Studies show evidence that use of HR-practices may encourage knowledge sharing of employees (Hislop, 2003; Cabrera and Cabrera 2005; Slagter, 2009; Camelo-Ordaz, et al. 2011). Examples of used HR-practices in this context are selection criteria, career management training, training and development, reward and performance appraisals, job design, and team building.
Liu & Liu (2011) investigated the relationship between HR-practices and individual knowledge sharing in high-tech industries. This study illustrated that HR-practices enhances individuals’ perceived self-efficacy and willingness to share knowledge, which facilitated knowledge sharing behavior among R&D professionals.
Slagter 2007 also investigated the relationship between HR-practices and knowledge sharing. Additional in this research was the relation between HR-practices and innovative behavior. She tested whether the availability of HR-practices predicted knowledge sharing and innovative behavior. Thereby she was the first to take age as a moderator in these relationships, instead of psychological processes. The findings suggested that training, self-development, career opportunities, flexible job design and intergenerational teams were significantly related to knowledge sharing. Training, self-development, career opportunities and intergenerational teams were significantly related to innovative behavior. Age only moderated the relationship between HR-practices and innovative behavior. A limitation in this study was that the focus on age was quite general and that it would be interesting to specify certain age groups. This is important in the context of the ageing workforce, since researchers start to realize that different generations also need different approaches (Dytchwald, Erickson and Morison, 2006).
when people hold more positive attitudes towards HR-practices, it will stimulate the preferred behaviours within the organization like knowledge sharing and innovative behavior.
Following subparagraphs describe the HR-practices used in current research and why these are thought to contribute to knowledge sharing and innovative behavior. These HR-practices are important and familiar HR-practices within COMPANY X and can be controlled and actively used by COMPANY X to steer employees’ behavior.
Training and Development
Professional development and training on a continuous base is important to professionals and knowledge workers in order to stay ahead of the competition in their professional field (Robertson et al. 2000). Employees are in a continuous changing environment, were stagnation means decline. Learning can be defined as “a planned and systematic effort to modify or develop knowledge, skills and attitudes through learning experiences, to achieve effective performance in an activity or range of activities”. Activities cover on- and off- the job training, training for younger workers and adult training, formal and informal training (Garavan, 1997).
COMPANY X has a Learning System, which contains all kinds of general and specific training available to every contracted employee. Thereby they also have learning academies, i.e. the HR-Academy, where they offer specific training applied to that field. Learning and development produces new knowledge and insights, which might foster the development of new and innovative ideas. This counts for every employee in the organization, no matter age.
Working Project Based
The focus in the article of Dorenbosch et al. (2005) was on the degree to which functional flexibility characterizes one’s job. Functional flexibility refers to the extent that the job enables the employee to assist or even replace colleagues. It originates from the idea that organizations should have employees that can quickly adapt to fluctuations in work processes within a fast moving environment. Company X operates in such a fast moving environment. To adapt to the high demanding environment, work must be done faster, with more flexibility and will become more projects based. Functional flexibility will therefore become very important when employees quickly move between different kinds of projects depending on the markets’ wishes.
Functional flexibility can be divided into multifunctionality and redundancy. Multifunctionality refers to the scope of tasks and the number of different tasks that are performed in a job or on a project. Working more projects based means working on more different tasks in a shorter time period within a broader scope since the job is changing more often. Working more project based might enrich jobs, and enriched jobs are more challenging and ask for more thinking according to Farr and Ford (1990) which could enhance knowledge sharing and innovative behavior. Redundancy refers to the number of workers that are qualified to perform a specific task. Jobs within COMPANY X designed to engage in a range of tasks can encourage people to get involved in other processes whereby they broaden their scope and work field. It may motivate older employees to enlarge their work field and engage in different work processes which in turn need and create more knowledge sharing and innovative behavior. Intergenerational Teams and Mentor Relationships
Cabrera et al. (2005) argue that when individuals spend more time together, they have more opportunities to share their knowledge. Not only cause of more frequent communication but also since this communication results in a shared language and codes. These social ties, which can be created in mentor relationships or within teams, will help to create environments conductive for knowledge sharing. The required interactions within intergenerational teams and mentor relationships facilitate knowledge sharing by creating structural and cognitive social capital, as well as it enhance the development of close relationships which has a positive effect on willingness to share (Cabrera et al. 2011). In mentoring relationships an experienced employee is linked to a less experienced, mostly younger, employee. It provides the older employees a chance to increase their value of usefulness and spread their knowledge and expertise. It is also a great opportunity for the organization since this encourages the knowledge flow.
In intergenerational teams it is very important that there is trust and group identification. When these relational dimensions are present, they can encourage positive attitudes toward knowledge sharing and thereby stimulate innovative behavior. Designing work around intergenerational teams supports the need to share knowledge with each other and to learn and use each other ideas and expertise, especially when rewards are based on team performance (Cabrera et al. 2011).
As can be seen, more attention is focused on the relation between HRM and knowledge sharing. However, explicit empirical data on the effect of HR-practices on innovative behavior is still scarce. More attention is needed towards the individuals and on the impact of HR-practices on knowledge sharing and innovative behavior; the bridge between these parts of literature needs to be strengthened. Thereby the role of age in the relationship has not been studied much in contemporary literature. Kooij, de Lange, Jansen and Dikkers (2007)emphasize the importance of HR-practices that match the needs of older workers to exploit the full potential of the aging workforce.
Research Questions
All sections above elaborated on the different concepts outlined in the research question. The goal of this thesis is to investigate the current job satisfaction and attitude towards HR-practices to see where this can be improved in order to set the right conditions to stimulate knowledge sharing and innovative behavior among the 50-65 workforce of COMPANY X. To reach this goal the following research question with its sub questions will be answered.
Research Question: Focusing on job satisfaction and attitudes towards HR-Practices, what can COMPANY X do to stimulate the 50-65 work population in their knowledge sharing and
innovative behavior?
Sub question 1: Is there a difference in the degree of knowledge sharing and innovative
behavior, job satisfaction and attitude towards HR-practices for the three different age groups under study?
Sub question 2: Is there a difference in job satisfaction for employees with low and high scores on knowledge sharing behavior?
Sub question 3: Is there a difference in job satisfaction for employees with low and high scores on innovative behavior?
Sub question 4: Is there a difference in attitude towards HR-Practices for employees with low and high scores on knowledge sharing behavior?
METHOD Research Design
Current research design was an explorative cross-sectional design using one-way analysis of variance to assess whether there are significant differences between groups. All analyses below are conducted with SPSS 17.0.
Sample
In scope for this research were all employees within COMPANY X with an age between 50-65 years. Out of scope were the employees from third-party services; employees in functions like cleaning and canteen that are outsourced. An online web-based questionnaire, created at www.thesistools.com, has been send to 274 employees. On behalf of the site leader a mass mail has been send out in order to ask employees to cooperate and to fill in the questionnaire. The questionnaire was available in Dutch and in English since there are foreign employees within COMPANY X (see appendix, for the invite and overview of the questionnaire). A link in the email directed employees towards the questionnaire where they are informed about the background and content of the questionnaire. Assurances of anonymity and confidentiality were explicitly given. After eight days, a reminder had been sent. In total it took three weeks to receive 237 responses, which created a response rate of 86.5%. After removal of questionnaires with missing values, a total number of 192 completed questionnaires remained, whereby the renewed adapted response rate was 70.1%.
Measurements
Personal Information
Some personal information was gathered like age, gender, work level, work department, contractual hours of work per week and years of employment for Company X.
Job Satisfaction
The short form of the Minnesota Satisfaction Questionnaire measures Job satisfaction, which is a widely used measurement (Weiss, Davis, England and Loftquist, 1967). By using this questionnaire I wanted to measure the opinion and feelings of employees about their current job. The satisfaction questionnaire contained 20 items. Twelve items were used to measure intrinsic job satisfaction, six items were used to measure extrinsic job satisfaction, and the additional two items were used to measure general job satisfaction. Intrinsic job satisfaction refers to satisfaction with certain factors in the job setting which offered prospects for activity, independence, variety, social status, moral values, security, social service, authority, ability utilization, responsibility, creativity and achievement. Extrinsic job satisfaction is the extent to which the employee was satisfied with received supervision, institution policies and practices, compensation, advancement, opportunities and recognition. General job satisfaction was measured by the satisfaction with co-workers and working conditions. The 20 items together measured job satisfaction.
HR-Practices
Current research measured the attitude towards four HR-practice used within COMPANY X. In order to assess the degree of attitudes possessed by persons and to be able to study a large number of people, the Semantic differential scale was used. This scale is developed by Osgood, Suci and Tanenbaum, (1957) to measure attitudes from the meaning, that people give to a word or concept that is related to an attitude object. The scale used here, consists of the bipolar adjectives negative and positive and has a continuum of seven points, the endpoint is exactly the opposite of the begin point and the midpoint has a neutral position.
Below you will find an overview of the four HR-Practices with a short description. It are specific COMPANY X HR-practices, therefore this measurement is not scientifically validated.
1) Training and Development: professional development and training. All courses available in the Learning System and the academies to train and develop yourself. Training includes e-learning, classroom training, mini-bytes or combinations thereof. 2) Working Project Based: Within Company X the work is already organized even more
on a project base. In the future this project based working will only develop to a larger degree.
3) Intergenerational Teams: this refers to the demographical composition of teams in departments. Does the team composition consist of multiple generations or is the composition very homogeneous.
Knowledge Sharing Behavior
The variable knowledge sharing behavior (KSB) was measured by 28 items on a five point behavioural frequency scale anchored from 1 meaning “never” and 5 meaning “always”. The items assess knowledge sharing behavior on the categories written contribution (WC), organizational communications (OC), personal interactions (PI) and communities of practice (CP). An example item for written contribution was: “I share documentation from personal files related to current work”. The 28 items used to measure knowledge sharing behavior are from a measurement developed by Yi (2009). He developed and validated a new scale for knowledge sharing behavior with desirable psychometric properties. His results provided evidence of good reliability of the measurement, the alpha for knowledge sharing behavior was (.73), for WC (.51), for OC (.92), for PI (.71) and for CP (.94).
Innovative Behavior
The variable innovative behavior (IB) was measured by means of 14 items on a five-point behavioural frequency scale anchored from 1 meaning “never” and 5 meaning “always”. The items assessed the individual innovative behavior of the employee. An example item was: “In your current job, how often do you experiment with new ideas and solutions?” The items to measure innovative behavior are from a measurement developed by Kleyson and Street (2001). They developed and tested a measure of individual innovative behavior, based on a literature review of individual level innovation studies. The reliability for this scale was (0.95)
Questions and Comments
RESULTS
The results section will discuss the statistical analyses on the data available from the questionnaires. This will be done in order to gain insights into the relationships between the variables job satisfaction, attitude towards HR-Practices, knowledge sharing behavior, innovative behavior and age. The following analyses were carried out:
• Reliability and Correlation Analyses
• One-Way Between-Groups analysis of variance (ANOVA) Reliability and Correlation Analyses
Table 1
Descriptive Statistics and Correlations
Variable Mean s.d 1 2 3 4 5
1. Age 54.58 3.56
2. Job Satisfaction 4.26 .30 .04 (.71)
3. Attitude towards HR-Practices 5.40 .87 -.14 .23** (.70)
4. Knowledge Sharing Behavior 2.90 .64 -.16* .21** .54** (.93)
5. Innovative Behavior 3.52 .69 -.05 .24** .44** .74** (.95)
N = 192
* p < 0.05 (2-sided). ** p < 0.01 (2 sided). Cronbach’s Alpha on Diagonal.
One-Way Between-Groups ANOVA analyses
In this part of the results section, one-way between groups ANOVA analyses will be employed to compare the mean scores of different groups. ANOVA compares the variance or variability between the different groups, believed to be due to the independent variable with the variability within each of the groups believed to be due to chance. Different ANOVA analyses will be conducted.
• First to compare the mean scores on knowledge sharing behavior and innovative behavior, job satisfaction and attitude towards HR-practices for the three different age groups.
• Second to compare the mean scores on job satisfaction for employees with low and high scores on knowledge sharing and innovative behavior.
• Last to compare the mean scores on attitude towards HR-practices for employees with low and high scores on knowledge sharing and innovative behavior.
The Three Different Age Groups
In this case, the three different age groups will be compared to see if they differ on their mean score on knowledge sharing and innovative behavior, job satisfaction and attitude towards HR-practices. The variable age is a recode variable, dividing age into three groups. The age groups are set for employees with an age between 50-54, 55-59 and 60-65 years.
There was no statistically significant difference at the p < .01 level in knowledge sharing behavior scores for the three age groups F(2,189) = 2.94, p = .06. The same counts for innovative behavior, job satisfaction and attitude towards HR-practices. There was no significant difference at the p < .01 level in innovative behavior scores F(2,189) = .81, p = .45, job satisfaction F(1,189) = .06, p = .94, and also not for attitude towards HR-practices F(2,189) = 1.76, p = .17 for the three age groups. This means that the age groups can be seen as equal regarding their scores on knowledge sharing and innovative behavior, job satisfaction and attitude towards HR-practices. Table 2 shows the mean and standard deviation for the three age groups.
Table 2
Descriptives for the three age groups on Knowledge Sharing behavior, Innovative Behavior, Job Satisfaction and Attitude towards HR-practices
Scores on knowledge sharing and innovative behavior range from 1-5, with higher scores indicating a higher degree of that behavior. Scores on job satisfaction range from 1-5, with higher scores indicating more satisfaction. Scores on attitude towards HR-practices range from 1-7 with higher scores indicating a more positive attitude.
Age 50-54 (n=104) Age 55-59 (n=63) Age 60-65 (n=25)
Mean (SD) Mean (SD) Mean (SD)
Knowledge Sharing Behavior 3.00 (.61) 2.90 (.67) 2.63 (.60)
Innovative Behavior 3.53 (.69) 3.56 (.60) 3.35 (.85)
Job Satisfaction 4.26 (.32) 4.28 (.25) 4.27 (.35)
Job Satisfaction and Knowledge Sharing Behavior
In this ANOVA analysis, the variable knowledge sharing behavior is recoded into two groups. The two different groups are now employees with low scores on knowledge sharing behavior (lower than average) and employees with high scores on knowledge sharing behavior (higher than average). It will be tested if the variance between these groups is due to the variable job satisfaction.
There was a statistically significant difference at the p < .05 level on job satisfaction for the high and low groups F(1,190) = 5.25, p = .02. The mean score for the group low (M=4.21, SD=.30) was significantly lower than it was in the high group (M=4.31, SD=.30). Despite reaching statistical significance, the actual difference in mean scores between the low and high groups was quite small. The effect size, calculated using eta squared was (.03). Cohen (1988) classifies (.01) as small effect, (.06) as a medium effect and (.14) as a large effect. Despite the small difference, it is proven that the variance between the groups is due to job satisfaction.
The job satisfaction measure exists of three different dimensions; intrinsic, extrinsic and general job satisfaction. Three ANOVA analyses will now be executed to test the two groups on mean scores on these three different dimensions to get a more specific insight in the different dimension of job satisfaction and the variance they cause in low or high scores on knowledge sharing behavior. To reduce the risk of a Type 1 error, I set a more stringent alpha value of .01.
Table 3
Descriptives for high and low scores on Knowledge Sharing Behavior for Job Satisfaction
Scores on job satisfaction range from 1-5, with higher scores indicating more job satisfaction. LOW refers to the group of employees who score beyond average on innovative behavior and HIGH refers to employees who score above average on innovative behavior.
There is a difference in job satisfaction for employees with low and high scores on knowledge sharing behavior. To improve knowledge sharing behavior among employees within the 50-65 work population you might improve the intrinsic job satisfaction. To see which specific parts of intrinsic job satisfaction can be improved, I employed extra ANOVA analysis at item level. The results showed that five out of twelve intrinsic job satisfaction items were significantly different at p < .05 for employees in the low and high groups. Activity: F(1,190) = 6.16, p = .01; Independence: F(1,190) = 4.78, p = .03; Variety: F(1,190) = 5.18, p = .02; Moral Values: F(1,190) = 5.54, p = .02; Ability Utilization: F(1,190) = 3.99, p = .04. The mean scores at these items in the low groups were significantly lower than the mean scores for employees with high scores at knowledge sharing behavior as can be seen in table 4. Despite its significance the calculated effect sizes were all low, (.02) or (.03) meaning that the actual differences in mean scores between the low and high groups are very small. Also the F-values are quite low, meaning less variability between the groups that is caused by the items themselves. Therefore these results must be interpreted with some cautiousness.
LOW (n=94) HIGH (n=98) Mean (SD) Mean (SD) Job Satisfaction 4.21 (.30) 4.31 (.30)
Table 4
Descriptives for high and low scores on Knowledge Sharing Behavior for five Intrinsic Job Satisfaction items
Scores on intrinsic job satisfaction range from 1-5, with higher scores indicating more intrinsic job satisfaction. LOW refers to the group of employees who score beyond average on innovative behavior and HIGH refers to employees who score above average on innovative behavior.
Attitude towards HR-practices and Knowledge Sharing Behavior
In this ANOVA analyses, the two different groups are again employees with low and high scores on knowledge sharing behavior. It will be tested if the variance between these groups is due to the attitude on HR-practices. First it will be tested if the variance between these groups is due to the average attitude towards HR-practices. When it is proven that the variance between the groups is due to this variable, the different HR-practices will be evaluated to get a more specific insight in the differences. HR-Practices in this measure consists of four practices; training, working project based, working in intergenerational teams and mentor relationships.
There was a statistically significant difference at the p < .05 level in attitude towards HR-practices for low and high scores on knowledge sharing behavior. F(1,190) = 56.37, p = .00. Table 5 indicates that the attitude towards HR-practices for those with a low scores (M=4.98, SD=.78) on knowledge sharing behavior were significantly lower than for employees who scored high on knowledge sharing behavior (M=5.81, SD=.75). The calculated effect size was large
LOW (n=94) HIGH (n=98) Mean (SD) Mean (SD) Activity
Being able to keep busy all the time
4.17 (.77) 4.42 (.61)
Independence
The chance to work alone on the job
4.33 (.65) 4.52 (.56)
Variety
The chance to do different things from time to time
4.23 (.71) 4.46 (.66)
Moral Values
Being able to do things that do not go into my conscience
4.21 (.65) 4.42 (.55)
Ability Utilization
The chance to so something that makes use of my abilities
(.20). It is proven that the variance between the groups is due to attitude towards HR-practices; the different HR-practices will now be analysed to get a more specific insight in the variance they cause in low or high scores on knowledge sharing behavior. To reduce the risk of a Type 1 error, I set a more stringent alpha value of .01.
There was a statistically significant difference at the p < .01 level in attitude on all HR-practices for low and high scores on knowledge sharing behavior. Training: F(1,190) = 8.56, p = .00; Working Project Based: F(1,190) = 41.31, p = .00; Working in Intergenerational Teams: F(1,190) = 30.79, p = .00; and Mentor Relationships: F(1,190) = 38.87, p = .00. The effect size, calculated using eta squared were respectively (.04), (.18), (.14), (.17). This means that only for training the effect size was small which means that the actual difference between the low and high group was quite small, despite its significance. For the other three HR-practice, there is a large effect size meaning larger differences between mean scores.
Table 5 indicated that employees with low scores on knowledge sharing behavior had a significant less positive attitude (M=4.34, SD=1.27) towards training as HR-practice than employees with high scores (M=4.91, SD=1.42) on knowledge sharing behavior. The same counts for the other HR-Practices. Employees with low scores on knowledge sharing behavior had a significant less positive attitude (M=4.90, SD=1.24) toward working project based than employees with high scores (M=5.95, SD=1.01). Employees with low scores on knowledge sharing behavior had a significant less positive attitude (M=5.37, SD=1.07) toward working in intergenerational teams than employees with high scores (M=5.95, SD=1.01). Finally employees with low scores on knowledge sharing behavior had a significant less positive attitude (M=5,37, SD=1.07) toward mentor relationships than employees with high scores (M=5,95, SD=1.01).
Thus there is a difference in attitude towards HR-Practices for employees with low and high scores on knowledge sharing behavior. To improve the knowledge sharing behavior among employees within the 50-65 work population, you might improve the attitude towards training, working project based, working in intergenerational teams and mentor relationships. Following section will discus the ANOVA on the mean scores on job satisfaction and HR-practices for employees scoring high and low on innovative behavior.
Table 5
Descriptives for high and low scores on Knowledge Sharing Behavior for Attitude towards HR-practices
Scores on attitude towards HR-practice range from 1-7, with higher scores indicating a more positive attitude. LOW refers to the group of employees who score beyond the average on knowledge sharing behavior and HIGH refers to employees who score above the average on knowledge sharing behavior.
Job Satisfaction and Innovative Behavior
In this case, the two different groups are employees with low and high scores on innovative behavior. It will be tested if the variance between these groups is due to job satisfaction. When it is proven that the variance between the groups is due to job satisfaction, the different dimensions of job satisfaction will again be evaluated to get a more specific insight in the differences.
There was a statistically significant difference at the p < .05 level on job satisfaction for the high and low groups F(1,190) = 9.35, p = .00. Table 6 shows that employees with low scores on innovative behavior also show lower job satisfaction (M=4.20, SD=.30) than employees with high scores on innovative behavior (M=4.33, SD=.30). Despite reaching statistical significance, the actual difference in mean scores between the low and high groups was quite small. The effect size, calculated using eta squared was (.05). Despite the small difference, it is proven that the variance between the groups is due to job satisfaction; the different dimensions intrinsic, extrinsic and general job satisfaction will now be analysed to get a more specific insight in the different dimension of job satisfaction and the variance they cause in low or high scores on knowledge sharing behavior.
Again one-way between-groups ANOVA was conducted to explore the impact of the different dimensions of job satisfaction on levels of innovative behavior. There was a statistically
LOW (n=94)
HIGH (n=98) Mean (SD) Mean (SD) Attitude towards HR-Practices 4.98 (.78) 5.81 (.75)
Training and Development 4.34 (1.27) 4.91 (1.42)
Working Project Based 4.90 (1.24) 5.95 (1.01)
Intergenerational Teams 5.37 (1.07) 6.17 (0.93)
significant difference at the p < .01 level on intrinsic job satisfaction for the high and low groups F(1,190) = 18,74, p = .00. Table 6 indicated that the intrinsic job satisfaction for those with a low score (M=4.18, SD=.38) on innovative behavior were significant lower than for employees who scored high on innovative behavior (M=4.40, SD=.32). The effect size, calculated using eta squared was (.09), meaning that the actual difference in mean scores between the low and high groups therefore is neither small nor large, but fine.
Table 6
Descriptives for high and low scores on Innovative Behavior for Job Satisfaction
Scores on job satisfaction range from 1-5, with higher scores indicating more job satisfaction. LOW refers to the group of employees who score beyond average on innovative behavior and HIGH refers to employees who score above average on innovative behavior.
So there is a difference in job satisfaction for employees with low and high scores on innovative behavior. To improve this behavior among employees within the 50-65 work population you might improve the intrinsic job satisfaction. To see which specific parts of intrinsic job satisfaction can be improved, again extra ANOVA analysis are done at item level. The results showed that six out of twelve intrinsic job satisfaction items were significantly different at a p <.05 level. We found that for Moral Values and Responsibility the test of homogeneity of variances was violated, which makes those F-tests invalid. Therefore, for those two ANOVA analyses I looked at results of the Brown-Forsyth test. Activity: F(1,190) = 17.47, p = .00; Independence: F(1,190) = 13.44, p = .00; Variety: F(1,190) = 12.54, p = .00; Moral Values: F(1,188) = 14.28, p = .00; Responsibility: F(1,190) = 5.22, p = .02; Creativity F(1,190) = 8.12, p = .01. In table 7 it can be seen that the mean scores for these items were significantly lower for employees with low score than for employees with high scores at innovative behavior. The calculated effect sizes were respectively (.08), (.07), (.06), (07), (.03) and (.04). Despite its
LOW (n=96)) HIGH (n=96) Mean (SD) Mean (SD) Job Satisfaction 4.20 (.30) 4.33 (.30)
significance, the actual differences in mean scores between the low and high groups are very small for responsibility and creativity and therefore this result must be interpreted with cautiousness. For the other four items the actual difference are medium and therefore these aspects of intrinsic job satisfaction might best be focused on to improve innovative behavior.
Table 7
Descriptives for high and low scores on Innovative Behavior for six Intrinsic Job Satisfaction items
Scores on intrinsic job satisfaction range from 1-5, with higher scores indicating more intrinsic job satisfaction. LOW refers to the group of employees who score beyond average on innovative behavior and HIGH refers to employees who score above average on innovative behavior.
Attitude towards HR-practices and Innovative Behavior
In this ANOVA, the two different groups are again employees with low and high scores on innovative behavior. It will be tested if the variance between these groups is due to the attitude towards HR-practices. First it will be tested if the variance between these groups is due to the average attitude towards HR practices. When it is proven that the variance between the groups is due to this variable, the different HR-practices will be evaluated to get a more specific insight in the differences. LOW (n=94) HIGH (n=98) Mean (SD) Mean (SD) Activity
Being able to keep busy all the time
4.09 (.77) 4.50 (.56)
Independence
The chance to work alone on the job
4.27 (.67) 4.58 (.50)
Variety
The chance to do different things from time to time
4.18 (.77) 4.52 (.56)
Moral Values
Being able to do things that do not go into my conscience
4.16 (.62) 4.48 (56)
Responsibility
The freedom to use my own judgement
4.08 (.72) 4.32 (.73)
Creativity
The chance to try my own methods of doing the job
There was a statistically significant difference at the p < .05 level in attitude towards HR-practices for low and high scores on innovative behavior. F(1,190) = 32.68, p = .00. The calculated effect size was large (.15). Table 8 shows that employees with low scores on innovative behavior also have a less positive attitude towards HR-practices (M=5.01, SD=.87) than employees with a high score (M=5.73, SD=.74). It is proven that the variance between the groups is due to attitude towards HR-practices; the different HR-practices will now be analysed to get a more specific insight in the variance they cause in low or high scores on innovative behavior. The four HR-practices are; training and development, working project based, working in intergenerational teams and mentor relationships. Again to reduce the risk of a Type 1 error, I set a more stringent alpha value of .01.
There was a statistically significant difference at the p<.01 level in attitude on all HR-practices for low and high scores on innovative behavior. Training and development: F(1,190) = 6.29, p = .01; Working Project Based: F(1,190) = 27.22, p = .00; Working in Intergenerational Teams: F(1,190) = 16.38, p = .00; and Mentor Relationships: F(1,190) = 20.75, p = .00. The effect size, calculated using eta squared were respectively (.03), (.13), (.08), and (.10). This means that only for training and development the effect size was small which means that the actual difference between the low and high group was quite small, despite its significance. For the other three HR-practice, there is a medium to large effect size meaning larger differences between mean scores.
Table 8
Descriptives for high and low scores on Innovative Behavior for Attitude towards HR-practices
Scores on attitude towards HR-practice range from 1-7, with higher scores indicating a more positive attitude. LOW refers to the group of employees who score beyond the average on knowledge sharing behavior and HIGH refers to employees who score above the average on knowledge sharing behavior.
Thus there is a difference in attitude towards HR-Practices for employees with low and high scores on innovative behavior. To improve the innovative behavior among employees within the 50-65 work population, you might improve the attitude towards training and development, working project based, working in intergenerational teams and mentor relationships. LOW (n=96)) HIGH (n=96) Mean (SD) Mean (SD) Attitude towards HR-Practices 5.01 (.87) 5.73 (.74)
Training and Development 4.39 (1.38) 4.88 (1.32)
Working Project Based 5.00 (1.22) 5.88 (1.10)
Intergenerational Teams 5.48 (1.13) 6.08 (0.93)
DISCUSSION Research Findings
As the workforce is aging rapidly, it becomes increasingly important to understand and know how age is related to different organizational outcomes and to examine contextual factors that enable older workers to show their competence at work. The goal of this study was to investigate what COMPANY X can do to stimulate knowledge sharing and innovative behavior among the employees aged between 50-65 years. I investigated the current job satisfaction and attitude towards HR-practices to see where this can be improved to stimulate knowledge sharing and innovative behavior among the 50-65 workforce of COMPANY X. I conducted an explorative cross-sectional study using web-based questionnaires to gather data and find answers on the research questions.
I will start to discuss the answers on the sub questions. The first sub question was is there a difference in the degree of knowledge sharing and innovative behavior, job satisfaction and attitude towards HR-practices for the three different age groups? Regarding the latter, employees were divided into three age groups, one 50-54 group, one 55-59 group and one 60-65 years group. One-way between groups ANOVA analyses are employed to compare the mean scores on those four variables for the three different groups. Against our expectations, there is no difference in the degree of knowledge sharing and innovative behavior, job satisfaction and attitude towards HR-practices for the three different age groups under study. This means that the age groups can be equally approached regarding the recommendations to improve knowledge sharing and innovative behavior.
attitudes (Kooij, Lange and Dikkers, 2007). Studying different conceptualization of age in this context may be a good suggestion for future research.
The second and third sub question searched for answers on the questions is there is a difference in job satisfaction for employees with low and high scores on knowledge sharing and innovative behavior? Again one-way between-groups ANOVA analyses are conducted. The results showed that there were differences in the intrinsic dimension of job satisfaction for employees with low and high scores on knowledge sharing and innovative behavior. To stimulate knowledge sharing behavior, COMPANY X might focus on the intrinsic job satisfaction and the results showed that the focus must be placed on aspects like activity, independence and variety within the job. But also moral values and utilization of abilities seemed important factors for more knowledge sharing behavior. Regarding the differences in job satisfaction for employees with low and high scores on innovative behavior the results showed that employees with higher mean scores on innovative behavior also scored significantly higher at the intrinsic items; activity, independence, variety, moral values, responsibility and creativity. To stimulate innovative behavior, COMPANY X might therefore focus on these aspects of job satisfaction.
Existing literature mainly focused on the relationship between HR-practices and knowledge sharing and innovative behavior, current literature now also shows that a more positive attitude towards these practices does help to stimulate these behaviours.
The fact that employees with more positive attitudes towards HR-practices also show more knowledge sharing and innovative behavior might also be explained by personality theories. The big five model of personality distinct five general personality traits; Extraversion, Neuroticism, Agreeableness, Conscientiousness and Openness to Experience. A specific trait related to extraversion is positive emotions. Specific traits related to Openness to Experience are fantasy, actions and ideas; these are important traits for innovative behavior (George and Jones, 2005). This could be an alternative explanation for the found results, that due to differences in personality traits, more knowledge sharing and innovative behavior is showed. Knowing this, COMPANY X can take these personality traits into account in their recruitment and selection procedure if they want to improve knowledge sharing and innovative behavior.
Practical Implications
Our findings have some important practical implications for COMPANY X. I identified relevant factors that help to answer the research question which read as follows: Focusing on job satisfaction and attitudes towards HR-Practices, what can COMPANY X do to stimulate the 50-65 work population in their knowledge sharing and innovative behavior? Below the practical recommendations will answer this question based on the results and conclusions written above.
Within these focus groups, you must first test whether they recognize and agree with the found results. Hereby you can check whether this research had good face validity according to the respondents, did it really measure what I aimed for, this is very important.
Literature found many support for the value of mentor relationships as predictor for knowledge sharing (Bryant, 2005). Current research shows that a more positive attitude towards mentor relationships also stimulates this behavior even as it stimulates innovative behavior. Regarding mentor relationships, I would therefore recommend COMPANY X to look for opportunities to set up mentor programs where the senior employees will be assigned as mentors. Currently good mentor programs are in place, though aimed to mentor high potential females, whereby the mentor is often an employee at a high work level. About 60% of the employees within this study are WL1, if you want to maintain the knowledge and expertise of this experienced senior population and stimulate innovative behaviours, it would be wise to set up mentor programs specifically for this sample. Not all senior employees would immediately be competent enough to fulfil this additional role properly, therefore training and guidance might be needed.
Attitude towards training and development was least positive. COMPANY X must figure out what can be improved within their learning management systems and academies for the senior population. Cabrera et al. (2005) argued that when employees receive training, their self-efficacy increases, they have more assurance of their capabilities and therefore are more willing to share knowledge. It is important that the learning and development systems are as custom made as possible and that it provides formats for effective learning by all generation. Like said before, training produces new knowledge and insights that foster the development of new and innovative ideas for the organization. It would be good to know what the senior employees think that can be improved or added to create a more positive attitude, which might increase the knowledge sharing, and innovative behaviours.
towards working in intergenerational teams also stimulate this behavior. Therefore I would recommend COMPANY X to pay attention to the team building regarding age in each department within the organization to stimulate knowledge sharing and innovative behavior. For the whole organization a good view and long term vision regarding the building of the workforce would the recommended. More attention must be paid towards this topic especially since the demographic changes forecast the enormous changes due to ageing and thereby the outflow of many experienced and knowledgeable employees. To avoid a gap, to ensure a healthy building of the workforce, and to stimulate more knowledge sharing and innovative behavior, more attention is needed regarding this issue.
Finally, a more positive attitude towards working project based also led to more knowledge sharing an innovative behavior. Working project based as an HR-practice has not been studied much yet, but flexible job design has, in relation to knowledge sharing and innovative behavior. Flexibility in working on many different projects will become the way of working in the future at least for much work within COMPANY X, and therefore is an important practice to investigate in more detail. Slagter (2007) showed that the availability of flexible job designs had a positive influence on knowledge sharing. Dorenbosch et al. (2005) argued that the conditions for innovative behavior are found in flexible job design. Since working project based is very common within COMPANY X it must be done properly, most effective and efficient. Within the focus groups it must be found what can be done to make project based working more attractive and what it is that can be improved.
Research Limitations
Every study has some limitations, so does this one. The first concerns the used sample; current research was performed within an R&D industry with a specific focus on age. This has an impact on the external validity and thus limits the possibility to generalize the research findings. The results and recommendation can however be generalized to the R&D site of Company X in Colworth (UK) since their age composition and ageing issues resemble the ones described in this study.
There are also some limitations regarding the measurements of the study. The measurement to assess attitude towards HR-practices was not validated. This can have impact on the content validity, attitude is a comprehensive concept, and it might not be likely that this measure covers the overall attitude towards HR-practices. Thereby this measure only measures the attitude towards the different HR-practices by means of one question, and so the items may not totally cover the content. Other limitations concern the short version of the MSQ that was used to test job satisfaction. This measure tested the underlying constructs by means of one item, it would have been better when these constructs were measured by more items wherefore the extended MSQ version is very suitable.
The results of the analyses regarding job satisfaction were also not very robust looking at the calculated effect sizes, and F-values, despite the significant results. The actual differences in mean scores between the employees in low and high groups were quite small and less variability between the groups was really caused by the independent variable job satisfaction. Due to the large sample, small differences can become statistically significant; therefore the practical importance is reconsidered. The little robust results and the low correlation between job satisfaction and knowledge sharing and innovative behavior can unfortunately not really underpin the claim that job satisfaction will really help to improve knowledge sharing or innovative behavior.
the assessment of that behavior from the employee him or herself, the line manager and a direct colleague. A 360-degree measurement can therefore be a better option to get a more balanced insight in the behaviours under study.
A last limitation to mention is the sole focus on the 50-65 work population. This focus was chosen deliberately, though it does no not give the opportunity to compare it with other age groups within the organization. This could have provided insights in differences or similarities between different generations to see if a special approach in essence is needed for the senior work population or that it would be beneficial for the whole organization.
Suggestions for Future Research
How can we take HRM within this field of research a step further? Current research took an explorative cross sectional approach and analysed quantitative data. A suggestion for future research might be to take a more qualitative approach to study the issues with more in depth interviews and maybe even in some case studies. Both give more insights in the underlying causal and interrelated mechanisms that could better explain the relationship between the variables under study.
