The effect of age diversity on relationship quality and knowledge transfer; investigating the moderating role of positive diversity beliefs
University of Groningen Faculty of Economics and Business
Human Resource Management
18 January 2015 Emmie Carabain W.A. Scholtenstraat 22-4 9712 KW Groningen 06-21585073 e.j.carabain@student.rug.nl Student number: 2338602 Supervisor: Dr. F.A. Rink Second supervisor: Dr. S. Täuber Word count: 6448
Abstract
This study predicted that age diversity has a negative influence on knowledge transfer and this relationship would be mediated by relationship quality. A quantitative research investigated effects of age diversity on knowledge transfer, mediated by relationship quality and moderated by positive diversity beliefs. Focusing on these topics, this study reveals that knowledge is more likely to be transferred in teams of similar ages than in teams of diverse ages. Also, this study found evidence for the mediating effect of relationship quality in the relationship between age diversity and knowledge transfer. Positive diversity beliefs, however, did not moderate these effects.
Effects of Age Diversity on Knowledge Transfer
European countries are dealing with one of the biggest challenges nowadays, namely the ageing and shrinking of the current workforce at the same time (DeLong, 2004). This challenge is a consequence of two trends in the demographic sector; increasing life expectations and reduced levels of fertility (Stam, 2009). The resulting shortage in the workforce makes ‘productive use of all human resources’ necessary (IZA Research Report, 2013). The cause behind this ageing workforce is the baby-boom generation, which has changed the composition of organizational workforces today and results in high levels of age diversity. This change is becoming increasingly salient now that there are insufficient younger employees to replace older employees in their positions (Lahti & Moilanen, 2005).
Older employees possess a lot of knowledge and expertise that are lost when they retire and are not being replaced. It is estimated that between 50 and 90 percent of corporate knowledge will be kept in employees’ minds (Campos & Sánchez, 2003). Those knowledge gaps can lead to costly disruptions in organizational performance (Martins & Meyer, 2012). So, in order to retain their know-how and experience, organizations need to stimulate intensive knowledge transfer between employees of different ages (Argote & Ingram, 2000).
Unfortunately, it is not yet known under which circumstances these negative effects of age diversity can be mitigated. I will therefore examine one such circumstance: Diversity beliefs. This concept was introduced by van Knippenberg, de Dreu & Homan (2004) and described as the degree to which workers have faith in emphasizing diversity. Research shows that if people develop positive expectations about working with different others, then collaboration will improve (van Dick, van Knippenberg, Hägele, Guillaume & Brodbeck, 2008). This has never been tested for age diversity. Therefore, this study will focus on positive diversity beliefs of age diversity for which I pose the following research question:
Will positive age diversity beliefs moderate the relationships between age diversity, relationship quality and knowledge transfer?
Thorough examination of the underlying causes of the problem of knowledge transfer in age diverse situations makes an important contribution to existing literature because this situation is never tested in much detail. Existing literature is often focused on the solution of simply letting older employees work longer in an organization. Yet this does not solve the problem that these older workers are not always inclined to transfer their knowledge to younger workers. Second, given that age diversity has a great influence on the functioning of teams and on performance as well (e.g. van Knippenberg & Schippers, 2007), it is important to gain a clear understanding of whether positive diversity beliefs can mitigate these effects.
task-relevant knowledge, skills and abilities (e.g. van Knippenberg et al., 2004). The same can be applied to relationship quality, if this factor indeed mediates the relationship between age diversity and knowledge transfer, managers can apply to that by investing in good relationships among workers.
This paper will start with explaining theory behind the different variables used. Second, the research method used to test the different hypotheses will be explained. Third, the discussion session including limitations, future research and implications will be described. Last, this study ends by a brief conclusion of this research.
Theoretical Background
Knowledge transfer has a multidimensional character that can occur at organizational, group or individual level (Argote &Ingram, 2000). At the individual level, knowledge transfer happens when knowledge is simply passed from one person to the other (Lind & Seigerroth, 2000; Jasimuddin, 2005). Knowledge represents ‘an accumulation of experience in the form of insight and wisdom, of which the person may have difficulty in communicating to others but can easily utilise in the performance of a particular task’ (Arif, Egbu, Alom & Khalfan, 2008: p.93). Knowledge transfer in organizations can also be described as the procedure of how one part of the organization (department, division, group, and team) is influenced by the knowledge of another part (Argote & Ingram, 2000).
(1967: p.4). An example of tacit knowledge is a master chef who knows all fine experiential facts of cooking a dish but he cannot fully capture those facts in a written recipe (Lee, 2012). This form of knowledge is different from explicit knowledge which can be codified and easily transferred (Nonaka, 1994). As a result, it is not always easy to simply transfer knowledge from one person to another.
The ageing workforce is important in cases of knowledge transfer because older workers possess more tacit knowledge because of their work experience, networks and work tenure (DeLong, 2004). Normally, employees have to work years for one organization to build such experience and network. This consists out connections that help employees explain problems efficiently and independently (Haarmann, Kahlert, Langenberg & Müller-Prothmann, 2009). Because the ageing workforce possesses more tacit knowledge, retirement of this older generation will create challenges for the organization to retain the knowledge.
(1989) stated that age diverse teams communicate in a lesser extent than age similar teams do. Third, these findings are in line with a meta-analysis of Joshi and Roh (2009), showing that there is a small negative correlation between age diversity and team efficiency. So, organizations need to stimulate intensive knowledge transfer between employees of different ages (Argote & Ingram, 2000). Only then organizations will remain competitive and innovative over time (Cavusgil, Calantone, & Zhao, 2003).
Importantly, however, social identity theory (SIT) predicts that age diversity in and of itself also makes it more difficult to build high relationship quality. This approach indicates how individuals see themselves and who they identify with; they ‘classify themselves and others into various social categories, such as organizational membership, religious affiliation, gender and age cohort’ (Ashforth & Mael, 1989: p.20). Accordingly, a young worker of about twenty years old will identify him- or herself with a team of similar ages because this team represents the self. This process leads to in-group favouritism and biases towards workers of other ages (Ashforth & Mael, 1989), and has a decreasing effect on the quality of relationships in age diverse teams (e.g., Billig & Tajfel, 1973; Locksley, Ortiz, & Hepburn, 1980).
refers to the development of shared expectations and social standards, is important for knowledge transfer because tacit knowledge is not amenable to enforcement by contract (Foos et al., 2006). However, members of different ages are less likely to trust each other (Billig & Tajfel, 1973). Finally, shared norms and values foster knowledge transfer because they create a shared understanding of collective goals and specify proper ways on how to collaborate together (van Wijk et al., 2008). Yet members of different ages often hold different work values resulting from shared experiences and events (Parry & Urwin, 2011). So, in age diverse teams, tie strength, trust and value systems are relatively low, which signals that the quality of the relationships among the members is poor. To conclude, I expect that high levels of age diversity within a work team will reduce knowledge transfer because quality of the relationship between team members will be reduced (in terms of social ties, trust and value systems). These expectations will lead into the following hypotheses:
H1a: The relationship between age diversity and knowledge transfer is negative.
H1b: The relationship between age diversity and knowledge transfer is mediated by relationship quality.
al., 2008). Likewise, research of van Dick et al. (2008) stated that positive diversity beliefs results in a more positive relationship between personality diversity and identification with the team. In line with this, Williams and O’Reilly (1998) have developed the information/decision-making perspective. This perspective proposes that diversity in teams can lead to more skills, knowledge about tasks, and abilities which are ‘distinct and non-redundant’ (van Knippenberg et al, 2004: p.1009), when it is emphasized that these broad range of knowledge are available to all different members. Members thus hold positive diversity beliefs, when they realize that their team gives them access to a broader set of resources, task relevant information, and enables them to make thorough decisions (van Knippenberg et al, 2004).
Research has indeed found that diverse teams developed more creative and innovative solutions when members held high levels of diversity beliefs than when they did not (Ancona & Caldwell, 1992; Bantel & Jackson, 1989; De Dreu & West, 2001). I will therefore investigate which effect positive diversity beliefs have on the relationship between age diverse teams and knowledge transfer. I propose that there is a positive moderating effect of positive diversity beliefs on the relationship between age diversity and knowledge transfer. If members have positive beliefs in age diversity, it will have a positive impact on the relationships. My last hypothesis will thus be:
H2: Positive diversity beliefs moderates the relationship between age diversity and knowledge transfer, such that age diversity is more positively related to knowledge transfer when positive diversity believes are salient.
Method Design and Participants
A two by two between-subject factorial design was used to test the hypotheses; age diversity (high vs. low) and positive diversity beliefs (salient vs. neutral). The participants were randomly assigned across the four experimental conditions. In each condition, participants were presented with a hypothetical work setting in which experimental manipulations were included. Participants were asked to “imagine being personally involved in this situation” and had to answer a series of questions about it. Participants’ answers were complete anonymously and their participation was fully voluntary. After having finished the questions, participants were thanked for their participation.
Data was derived from 104 respondents (N=104), who filled in an online questionnaire made in Qualtrics. All respondents were contacted through my own network channels, which were Facebook, friends and family, or e-mail. I aimed for 100 respondents but ended up with 139. However, I included two attention checks in the questionnaire. The first check asked if they still knew the person who they were supposed to be in the beginning of the questionnaire, for example “were you working in a diverse or homogeneous team in terms of age?” This check was significant (see below) and therefore no participants were deleted according to this check. The second check was a random statement between the dependent measures asking participants to choose the answer “strongly agree”. A total of 35 participants had failed this attention check,
which means that they had not paid attention to the statements in the questionnaire. They were
65. 51.9% of them were female (N=54), 50% studied at university level, and 43% were employed for wages.
Manipulation of Age Diversity
Age diversity was manipulated by informing participants that all team members were either of similar age (homogeneous condition), or of different ages, with older workers being around 63 years old and younger works being around 25 years old (diversity condition). For a full description of the manipulation, see Appendix A. This manipulation was checked with one statement at the end of the questionnaire; “were you working in a diverse or homogeneous team in terms of age?” Possible answers were (1) “I was working in an age diverse team” and (2) “I was working in a homogeneous team in terms of age.” A two by two ANOVA with age diversity and positive diversity beliefs (see below) as independent factors showed that only age diversity was significant (F(1,102) = 77.22, p = .00, Magediverse = 1.06, Magesimilar = 1.71). There was no
main effect for diversity beliefs, F(1,102) = .51 nor an interaction effect F(1,102) = .02.
I further checked of which age category participants were thinking during the questionnaire. Results showed that participants filled in a diverse range of answers. Some people said a young member is “someone new to the job” and another said “25”. Only taking the ages, it showed that the perceived age of a young member was 24 years old (M = 23.54, SD = 4.64) and the perceived age of an older member is about 48 years old (M = 47.66, SD = 9.02).
Manipulation of Positive Diversity Beliefs
diversity.” Possible answers were (1) “Yes” and (2) “No.” A two by two ANOVA with age diversity and positive diversity beliefs as independent factors showed that diversity beliefs and the interaction effect were significant: F(1,102) = 25.58, p = .00, Mbeliefspresent = 1.14, Mbeliefsabsent
= 1.57 for diversity beliefs, and F(1,102) = 5.00, p = .03 for the interaction effect. However, there was no main effect for age diversity, F(1,102) = 2.45. Manipulations of positive diversity beliefs and age diversity led to a two-by-two factorial design, shown in Table 1.
Measures
All questions were measured by using a seven point Likert scale. The answers ranged from 1 till 7; 1 was meaning “strongly disagree” and 7 was meaning “strongly agree.” All full scales are presented in Appendix B.
Knowledge transfer. To measure knowledge transfer, the main dependent variable, nine statements were used (α = .94) adapted from Grutterink, Van der Vegt, Molleman and Jehn, (2013) and Holste and Fields (2010). For example “I would willingly share my new ideas with my team members” or “I think the other members of my team know in detail what I know and what I am capable of” or “I would be willing to pass on my personal work experience in this work team.” Originally there were 10 items for the scale of knowledge transfer but one item slightly lowered the reliability of the scale (α = .93 vs. α = .94), and was therefore excluded for further analyses.
Relationship quality. Relationship quality was measured by 12 existing statements from
frequently interact with my team members”; and six items for being valued (α = .95), for example “I would feel that my team members value my input.”
Supplementary Measure
Positive diversity beliefs. In addition to manipulating positive diversity beliefs, I also measured this concept by five statements from Homan (2010). These questions focused on how participants personally see positive diversity beliefs. For example: “I think teams that are diverse
in age usually communicate more often than teams that are homogeneous in age” (α = .81).
Factor Analysis
The factorability of the scales of knowledge transfer and relationship quality was examined. A principal components factor analysis using varimax showed that there were two clear factors with an Eigenvalue higher than 1, representing the scale of knowledge transfer and the scale of relationship quality. The factor loadings of both scales can be found in Table 2.
Another principal components factor analysis using varimax was performed to focus on the three subscales of relationship quality; trust, being valued and tie strength. This factor analysis showed that one item of trust (“I would discuss issues and problems openly in this team”) belonged to the factor of tie strength. Items of being valued showed several cross-loadings, for example “I would feel that my team members value my input” had a primary loading of .64 on the being valued factor and a cross-loading of .60 on the factor of trust. Because of the several cross-loadings and the first factor analysis (showing that there were only two factors with Eigenvalue higher than 1) the three subscales of relationship quality were analyzed as one scale,
Control Variables
In this study, two control variables were used to see their influence on the dependent variable; work experience and position. Work experience was used because it may influence how people look at their working life; Yi and Uen (2006) stated that work experience causes a faster adjustment to new situations and it will affect impressions of employees; they are not easily surprised about, for example a culture shock. They also have an improved ability to better understand information given by the company. Working position was used as a control variable because people who exert a higher position may be less inclined to transfer knowledge to people with a lower position (Yi & Uen, 2006). Working position was measured in several divisions, for example “operational staff”, “manager” or “executive staff.”
Results Descriptive Statistics
Hypotheses Testing
This study proposed that age diversity is negatively related to knowledge transfer, and that the relationship between age diversity and knowledge transfer is mediated by the quality of the relationship. I further hypothesized a moderating effect of positive diversity beliefs on the relationship between age diversity and knowledge transfer.
Knowledge transfer. A two by two ANOVA was performed to examine independent and joint effects of age diversity and positive diversity beliefs on knowledge transfer. Results showed only a main effect of age diversity, F(1,100) = 7.29 p = .008, η2 = .068, d = -0.57. There was no significant effect of positive diversity beliefs on knowledge transfer (p = .46, η2 = .005), and neither an interaction effect (age diversity x positive diversity beliefs) on knowledge transfer (p = .75,η2 = .001). This means that on average, participants were more likely to share knowledge in teams of similar ages (M = 5.57, SD = .93) than in teams of high age differences (M = 4.94, SD = 1.27), regardless of their diversity beliefs. Adding the control variables working experience and working position did not influence this effect. The effect remained significant, F(1,95) = 7.17 p = .009, η2 = .070, d = -0.56. Results can be found in Table 5. Accordingly, hypothesis 1a can be supported; age diversity has a negative influence on knowledge transfer.
differences (M = 5.20, SD = .98), regardless of their diversity beliefs. Adding the control variables working experience and working position did not influence this effect. The effect remained significant, F(1,95) = 6.63, p = .01, η2 = .065, d = -0.52. Results can be found in Table 6. As such, the second hypothesis reflecting the moderating effect of positive diversity beliefs can be rejected.
Mediation. The SPSS PROCESS bootstrapping macro for simple mediation (Preacher & Hayes, 2004) was performed to show the effect of relationship quality on the relation between age diversity and knowledge transfer. This test showed that relationship quality indeed significantly mediated the effect of age diversity on knowledge transfer b = .41, Boot SE = .18, LL95%CI = .11, UL95%CI = .81. This was not affected by adding control variables work experience and work position, the mediation effect remained significant; b = .42, Boot SE = .18, LL95%CI = .10, UL95%CI = .82. So while age diversity significantly predicted knowledge transfer (F(1,100) = 7.29 p = .008, η2 = .068, d = -0.57), adding relationship quality as a mediator reduced the significance of this relationship shown by Sobel’s test (b = .54, t = 2.73, p = .0108). Results of age diversity and relationship quality predicting both knowledge transfer showed that relationship quality was significant (b = .78, t = 11.44, p = .00) but, age diversity was not significant (b = .16, t = 1.09, p = .28). Following the significant effect of the mediation, it can be concluded that hypothesis 1b reflecting the mediated effect of relationship quality, can be supported.
Supplementary Analysis
diverse in age usually perform better than teams that are homogeneous in age.” It is hypothesized that personal diversity beliefs will moderate the relationship between age diversity and knowledge transfer. Linear regression was used to predict the effect of personal diversity beliefs on knowledge transfer. The independent variables were standardized prior to the analyses (Aiken & West, 1991). Table 7 demonstrates the results of the different levels. Model 1 is the first step of the analysis, where work position and work experience were added as control variables. The second step includes entering standardized age diversity and personal diversity beliefs (model 2). The third model added the interaction between age diversity and personal diversity beliefs. Knowledge transfer was added as the dependent variable to all three models. A significant regression was found for models 2 and 3; model 2 (F(1,100) = 8.01, p = .00), with an R2 of .25, and model 3 (F(1,100) = 8.77, p = .00), with an R2 of .32. Within model 2, a positive coefficient was found for age diversity (B = .28), which is interesting because this contradicts the main model of this study showing that age diversity lowers knowledge transfer. Also, a positive coefficient was found for personal diversity beliefs (B = .49), meaning that this will also increase knowledge transfer. Besides, a significant interaction effect was found between age diversity and personal diversity beliefs (B = -.30, t = -3.02, p = <.01); indicating that this interaction effect has a decreasing effect on knowledge transfer. Control variables work experience and work position (model 1) did not have any influence on these significant effects.
checks. Running a two way ANOVA on this sample showed that age diversity still have a significant relationship on knowledge transfer F(1,59) = 15.47, p = .00, η2 = .208, d = -1.14. But this time, there was also a significant effect of positive diversity beliefs on knowledge transfer F(1,59) = 4.40, p = .04, η2 = .069, d = 0.41, which was not the case in the main sample of 104 participants. This test showed no interaction effect (age diversity x positive diversity beliefs) on knowledge transfer.
Performing the same test on relationship quality showed that only age diversity has a significant effect on relationship quality F(1,59) = 10.15, p = .00, η2 = .147, d = -0.92. No moderating effect of positive diversity beliefs was shown and neither an interaction effect. Concluding, taking this sample, hypothesis 1a stating that age diversity influences knowledge transfer can be supported. Hypothesis 2 stating that positive diversity beliefs moderates the relationship between age diversity and knowledge transfer can be rejected because it only showed a significance effect on knowledge transfer.
Discussion
This study was intended to investigate whether age diversity had a negative effect on knowledge transfer. Besides, the moderating role of positive diversity beliefs was tested of which was expected that this would have a positive effect on the relationships. Simultaneously, relationship quality was tested if it had a mediating effect on the relationship between age diversity and knowledge transfer.
Taken everything together, the results support hypothesis 1a, that knowledge will be more likely transferred in age similar teams than in age diverse teams (see Table 8). The results also supported hypothesis 1b that the relationship between age diversity and knowledge transfer was mediated by relationship quality. There was, however, no significant influence of positive diversity beliefs on any of the relationships. Thus, hypothesis 2 can be rejected. This means that it does not matter if the manager emphasizes positive diversity beliefs or not when knowledge needs to be transferred in age diverse or age similar teams.
relative young age, it could be possible that they perceive it according to this theory and are thus more willing to learn and transfer knowledge. Second, research on manipulation studies (Kidd, 1976) showed that participants’ responses to a hypothetical work setting can bias answers to subsequent self-reporting questions. Because supplementary analysis of this study was tested with self-reporting questions about positive diversity beliefs, answers to these questions could be biased due to the previous manipulation. This may have cause the contradicting result of this study.
Theoretical Implications
Multiple theoretical implications are offered by this study to understand the influence of age diversity on knowledge transfer. First, assumptions of previous literature stating that age diversity decreases knowledge transfer was confirmed by this study. This finding goes against the common solution to let older people work longer in the organization (e.g. DeLong, 2004), as knowledge transfer between younger and older workers does not occur automatically. Second, the importance of the quality of relationships in the process of knowledge transfer was also confirmed by this study. Furthermore, tie strength, trust and being valued indeed reflected relationship quality (e.g. van Wijk et al., 2008). Finally, the fact that positive diversity beliefs did not moderate any of the relationships suggests that literature on this topic should be interpreted with care. Evidently, positive diversity beliefs do not always have a large influence on team functioning (van Knippenberg & Schippers, 2007).
Limitations
This study had to deal with several limitations. First, the use of manipulated variables had already some limitations itself. Namely; (1) it can be misinterpreted by the participants, they can
not generalizable because it is no field study (Perdue & Summers, 1986). These limitations can be solved by doing the same research in a field study.
Second, the manipulation checks did not work out completely. On average, they did work but if participants who failed all the manipulation checks were deleted from the dataset, the sample size decreased from 139 to 63. To overcome this problem it might be helpful to add sentences of the scenario above the statements of the questionnaire so that participants are continuously reminded of their situation.
Third, data was derived mainly from students which might mean that this group is not a good representation of employees in a work team. It is possible that students have not worked with older workers before so they might not know how they will react in teams set up by the manipulation. Therefore, it is important to test the hypotheses in a field study among real life work teams. Participants which are already working in teams might have a better understanding of what it means to be working with others who are different in terms of age.
Fourth, because data was mainly derived from Dutch speaking participants and the questionnaire was written in English, it might be that some of the participants did not understand everything correctly. By adding an option in the beginning to let participants choose the language of the questionnaire, it will solve the language problem.
Directions for Future Research
There are several interesting paths to investigate for future researchers. For example, future work could focus on another moderator instead of positive diversity beliefs. Diversity training for all employees could be an interesting moderator to see if training about diversity can change mindsets of the employees. Rather than let only the manager emphasize that diversity is a good thing, one should focus on training about diversity to all employees. Improving the beliefs of employees about diversity and continuously convincing them with the positive aspects of diversities creates a more favorable mindset (Homan, Greer, Jehn & Koning, 2010). Diversity training can also be a solution to workplace discrimination, stereotyping and prejudice (King, Dawson, Kravitz, & Gulick, 2010). The purpose of diversity training is to let people learn work successfully with diverse people (Bezrukova, Jehn, Spell, 2012). These reasons can lead to better relationship quality between people and therefore better knowledge transfer.
The effect of in-group favoritism on knowledge transfer is another interesting topic for future researchers. In-group favoritism is most of the times associated with strong social networks within the group. It includes that members of their own group are more liked than members of the out-group (Argote & Ingram, 2000). This can have a negative effect on knowledge transfer; teams with strong in-group favoritism can have more troubles with transferring their knowledge to out-group members. Therefore, research should focus on how this in-group favoritism will affect the relationship between age diversity and knowledge transfer in teams. In-group members can create negative stereotypes of out-group members which lead to depersonalize and even create a social distance to these members (Ashforth & Mael, 1989). Ashforth and Meal (1989) also stated that perceptions of out-group members are usually seen as negative. According to these facts, it is expected that in-group favoritism will negatively moderate the relationship between age diversity and knowledge transfer.
Conclusion and Practical Implications
This study has proven that age diversity indeed has a negative influence on knowledge transfer in teams and that relationship quality significantly mediates this relationship. Meaning that to increase knowledge transfer in teams, teams should be composed of similar ages and with good relationship quality. Managers can do this by composing teams with special attention to these topics. It does not matter if a manager emphasizes positive diversity beliefs in a team or not because this moderator did not show any significant influence.
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TABLES OF STATISTICS Table 1
The Factorial Manipulation Design
High age diversity &
Positive diversity beliefs 1
Low age diversity &
Positive diversity beliefs 2
High age diversity &
Control (no diversity beliefs shown) 4
Low age diversity &
Control (no diversity beliefs shown) 3
Table 2
Rotation Component Matrix – Factor Analysis
Component Relationship
quality
Knowledge transfer I would allow any of my team members to observe me, in order to let
them better understand and learn from my work.
.304 .802
I would fully collaborate with any of my team members, in order to let them better understand and learn from my work.
.329 .794
I would willingly share my new ideas with my team members. .294 .811 I would willingly share my personal rules of thumb and insights into our
common task.
.199 .838
thought them to be important.
I think the other members of my team are aware of my knowledge and expertise.
.492 .685
I would be willing to pass on my personal work experience in this work team.
.335 .665
I think the other members of my team know in detail what I know and what I am capable of.
.481 .632
I think the other members of my team have an accurate view of what I know.
.511 .667
I would trust my fellow members in my work team. .735 .260
I would rely on my team members. .710 .224
I would have complete confidence in my team members' ability to perform tasks.
.718 .300
I would discuss issues and problems openly in this team. .668 .485 I would frequently interact with my team members. .683 .450 I would feel that I have close working relationships with my team
members.
.722 .434
Table 3
Component Matrix of Relationship Quality – Factor Analysis
Component Being
valued
Tie strength
Trust
I would trust my fellow members in my work team. .301 .459 .625
I would rely on my team members. .213 .206 .873
I would have complete confidence in my team members' ability to perform tasks.
.360 .427 .560
I would discuss issues and problems openly in this team. .352 .831 .245 I would frequently interact with my team members. .343 .783 .308 I would feel that I have close working relationships with
my team members.
.400 .645 .430
I would feel valued during the interaction with my team members.
.492 .435 .633
I would feel that my team members value my input. .643 .207 .601 I would feel respected during the interaction with my team
members.
.852 .370 .223
I would feel completely accepted by my team members. .746 .471 .319 I would feel that my team members respect my efforts. .802 .291 .334 I would feel that my team members perceive me as a full
team member.
Table 4
Descriptive Statistics and Variable Correlations
Variable M SD 1 2 3 4 5 1. Working experience 3.12 1.31 2. Working position 3.78 2.69 -.27** 3. Age diversity 1.53 .50 -.02 .07 4. Relationship quality 5.48 1.07 .02 .13 .25* 5. Knowledge transfer 5.35 1.09 -.02 .74 .26** .77** 6. Positive diversity beliefs 5.38 1.35 -.19 .34** -.23* .15 .15
**, Correlation is significant at the 0.01 level (2-tailed)
*, Correlation is significant at the 0.05 level (2-tailed)
Note: N=104 participants.
Table 5
Two-Way ANOVA Knowledge Transfer
Source df SS MS F p
Work experience (control) 1 .02 .02 .02 .90
Work position (control) 1 .59 .59 .51 .48
Age diversity 1 8.37 8.37 7.17 .01
Positive diversity beliefs 1 .59 .59 .50 .48
Table 6
Two-Way ANOVA Relationship Quality
Source df SS MS F p
Work experience (control) 1 .42 .42 .38 .54
Work position (control) 1 2.21 2.21 1.98 .16
Age diversity 1 7.41 7.41 6.63 .01
Positive diversity beliefs 1 .02 .02 .02 .89
Table 7
Linear Regression for Variables predicting Knowledge Transfer
Model 1 Model 2 Model 3
Variable: B SE B β B SE B β B SE B β Controls Work experience Work position Main effects .01 .08 .12 .12 .01 .08 .12 .02 .10 .10 .11 .02 .06 -.01 .10 .10 .06 -.01 Age diversity .28 .10 .25** .28 .09 .25 ** Personal diversity beliefs Interactions .49 .10 .44** .50 .10 .44 ** Age diversity x personal diversity beliefs -.30 .10 -.26 ** R2 .01 .25 .32
Note: all variables were standardized
**, significant at the 0.01 level
Table 8
Means and Standard Deviations for Knowledge Transfer in the 2 (age diversity: absent/present) by 2 (positive diversity beliefs: absent/present) Design
No positive diversity beliefs Positive diversity beliefs
FIGURES
Appendix A Manipulation Studies Age diversity high + positive diversity beliefs
Please imagine the following situation:
You are working in a work team of company X, you have been working in this team for quite some time. You are responsible for achieving collective goals. Together with your team members you are working on complex tasks that require problem solving. Your team consists of six members and is highly diverse in terms of age. This means that three members are relatively young, while the other three members are relatively old (see figure). So you are very different from each other in this respect.
Your manager composed your work team in this way because this person values age diversity. Your manager thus beliefs that age differences represent a positive feature of your team that you could benefit from.
Please give your answers based on this situation.
Age diversity low + positive diversity beliefs Please imagine the following situation:
You are working in a work team of company X, you have been working in this team for quite some time. You are responsible for achieving collective goals. Together with your team members you are working on complex tasks that require problem solving. Your team consists of six members and is highly homogeneous in terms of age. This means that all members are of the same age (see figure). So, you are very similar to each other in this respect.
Your manager had no other choice than to compose your work team in this way. Note however, that this person considers diversity to be a good thing in teams. Your manager thus actually beliefs that age differences represent a positive feature of teams that members could benefit from. Please give your answers based on this situation.
Age diversity high + control
Please imagine the following situation:
You are working in a work team of company X, you have been working in this team for quite some time. You are responsible for achieving collective goals. Together with your team members you are working on complex tasks that require problem solving. Your team consists of six members and is highly diverse in terms of age. This means that three members are relatively young, while the other three members are relatively old (see figure). So you are very different from each other in this respect.
Please give your answers based on this situation.
Age diversity low + control
Please imagine the following situation:
You are working in a work team of company X, you have been working in this team for quite some time. You are responsible for achieving collective goals. Together with your team members you are working on complex tasks that require problem solving. Your team consists of six members and is highly homogeneous in terms of age. This means that all members are of the same age (see figure). So, you are very similar to each other in this respect.
Appendix B Measurement Scales Knowledge transfer
1. I would allow any of my team members to observe me, in order to let them better understand and learn from my work.
2. I would fully collaborate with any of my team members, in order to let them better understand and learn from my work.
3. I would willingly share my new ideas with my team members.
4. I would willingly share my personal rules of thumb and insights into our common task. 5. I would willingly share the latest rumors going around the team, if I thought them to be
important.
6. I would be willing to learn from personal work experiences of my team members. 7. I would be willing to pass on my personal work experience in this work team. 8. I think the other members of my team are aware of my knowledge and expertise.
9. I think the other members of my team know in detail what I know and what I am capable of.
10. I think the other members of my team have an accurate view of what I know.
Relationship quality Trust
1. I would trust my fellow members in my work team. 2. I would rely on my team members.
4. I would discuss issues and problems openly in this team. Tie strength
5. I would frequently interact with my team members.
6. I would feel that I have close working relationships with my team members. Being valued
7. I would feel valued during the interaction with my team members. 8. I would feel that my team members value my input.
9. I would feel respected during the interaction with my team members. 10. I would feel completely accepted by my team members.
11. I would feel that my team members respect my efforts.
12. I would feel that my team members perceive me as a full team member.
Positive diversity beliefs
1. I think that diversity is an asset for our team. 2. I think that diversity is good.
3. I will enjoy working together with diverse team members. 4. I feel enthusiastic about diversity.
